Package: ecgpuwave Priority: optional Section: science Installed-Size: 212 Maintainer: Benjamin Moody Architecture: amd64 Version: 1.3.3-0~pn1 Depends: libc6 (>= 2.2.5), libgcc1 (>= 1:4.1.1), libgfortran3 (>= 4.6), libquadmath0 (>= 4.6), libwfdb10 (>= 10.5.11) Filename: pool/main/e/ecgpuwave/ecgpuwave_1.3.3-0~pn1_amd64.deb Size: 61062 MD5sum: cae7d6435d4381d1c01ac5ee56ab6d4d SHA1: 355d75435b2be7a1bc7891cdeb3de8e1b480cc25 SHA256: c691082099166ae9c7185aaf71497ca60b86f0136ee663fbc17f1ddb5dc88253 SHA512: ea6bcc88deafb10b4e6ed561613e59213244298c56f643ec35caf9f2e7515900f2a5f9d467f5e3007e9073b4237f35af1d677fc98455e866f44b86ee55f8e103 Description: QRS detector and waveform limit locator ecgpuwave analyses an ECG signal, detecting the QRS complexes and locating the beginning, peak, and end of the P, QRS, and ST-T waveforms. The QRS detector is based on the algorithm of Pan and Tompkins with some improvements that make use of slope information. Optionally, QRS annotations can be provided as input, permitting the use of external QRS detectors such as sqrs or manually-edited annotations. Package: islandhack Priority: optional Section: net Installed-Size: 72 Maintainer: Benjamin Moody Architecture: all Version: 0.4-0+pn1 Depends: libwww-perl, libhttp-daemon-perl, openssl, libislandhack0 (>= 0.4-0+pn1), perl:any Filename: pool/main/i/islandhack/islandhack_0.4-0+pn1_all.deb Size: 23034 MD5sum: 10504af1791517215d63d32d6c14b978 SHA1: cb7c57d73b5b4f0036364039b144564a29a92149 SHA256: c8428f7673a67c77c221fe43fbd8e0f55564d537b5446f76a604cfa79935b7d1 SHA512: 1fe0969e0a03ef1d28c5c7886e3ccbd9efb0a5a2b3627844e3f813354c985b9e1bea44652da6877ac00a4a3ef86fd005ea59e14cb4df5785eb0b76ceba594684 Description: run a program with simulated WWW access islandhack runs a program in an environment that provides simulated access to HTTP and FTP sites, serving all files from a local cache. It can be used to run programs that expect to be able to download particular files from the Web, without actually relying on remote servers or connecting to an outside network at all. Package: islandhack Priority: optional Section: net Installed-Size: 84 Maintainer: Benjamin Moody Architecture: amd64 Version: 0.1-0+pn1 Depends: libwww-perl, libhttp-daemon-perl, openssl, libc6 (>= 2.4), perl Pre-Depends: multiarch-support Filename: pool/main/i/islandhack/islandhack_0.1-0+pn1_amd64.deb Size: 14376 MD5sum: f7c42a14a58f137510ae5323f393fab5 SHA1: 0871e66db5ea905c32f58c6041ce0cf3178979e4 SHA256: c4a905bec2334e9a2e3ec40d27de37f2c9727ea70a54814ee1838dab2f91d34c SHA512: 0861283b4eaee6dc91a76ea5a8c9664ed6754a69426a94ee36bea9b3c2c9fee03228980aa2a561d3978ca3b589809b804b0f554a6b63d7915cf3c9f6e4bbea9d Description: run a program with simulated WWW access islandhack runs a program in an environment that provides simulated access to HTTP and FTP sites, serving all files from a local cache. It can be used to run programs that expect to be able to download particular files from the Web, without actually relying on remote servers or connecting to an outside network at all. Package: keras-doc Priority: optional Section: doc Installed-Size: 2911 Maintainer: Debian Science Maintainers Architecture: all Source: keras Version: 2.2.2-0+pn1 Suggests: python3-keras Filename: pool/main/k/keras/keras-doc_2.2.2-0+pn1_all.deb Size: 976302 MD5sum: aa7a64753eab7c8cce6776405b52d979 SHA1: 97a197d33efe4a2bafe2dfa2c684987b75b606ab SHA256: 4dedbe2e96ae5e1d29f109ff9e2a0a1a5667cf72d2fde8b5383f410a5ca29cd0 SHA512: e9b0b68c8c66df486760a9cd1285007de774e3629c07b5ee424af5e427606a897737e5fb28e636eae480b9dd3310d2bee685e846c78ff63e62b6d0d38e642763 Description: CPU/GPU math expression compiler for Python (docs) Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation. . Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing). . It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian, but coming up). . This package contains the documentation for Keras. Homepage: http://keras.io/ Package: libislandhack0 Priority: optional Section: net Installed-Size: 57 Maintainer: Benjamin Moody Architecture: amd64 Source: islandhack Version: 0.4-0+pn1 Depends: libc6 (>= 2.4) Filename: pool/main/i/islandhack/libislandhack0_0.4-0+pn1_amd64.deb Size: 15828 MD5sum: 41982e69cdc3a15e0ad85e1d4fb82dfb SHA1: 256eeda73cc66386ca46a9800a7b26e8f1094be5 SHA256: ce706ae7cf85a7e43488593c099e8e9ba3b09001aa8cf05cd4e377607ec25e54 SHA512: e24c8ec73adf0e09b30e02696778a38c59674836b8d73c25e8a03c573050d80a3f8f3aaad1b215a009c5613f0907c592d4a6fa252e6ac26fc28edb63f29ed2e1 Description: library to provide a fake certificate authority This package contains a library which can be used to force programs to trust a particular fake certificate authority. It is used by the islandhack package in order to provide simulated access to HTTPS sites. Multi-Arch: same Package: libopencv-calib3d-dev Priority: optional Section: libdevel Installed-Size: 2496 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-calib3d-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 531798 MD5sum: b94db379e1cd2ed66d8462a141f27c40 SHA1: 4e5f9e2b1535043c0d91f4aae147e8069ba198fa SHA256: 030a7c11aa18b898c53bf8f6665ecb705370f3e3368fd9aa581eff566cf584a4 SHA512: 06cfd4746907ef8e9910c5b14b2ab3517a8a25f223f445815a06ed4dd3a5932540b57e542c205d3114f63dfa8fa78ba3cbcf44a01b978999bfa5b2b7a1bcaa81 Description: development files for libopencv-calib3d3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Camera Calibration library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-calib3d3.2 Priority: optional Section: libs Installed-Size: 1414 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-features2d3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:4.0), libopencv-core3.2, libopencv-flann3.2, libopencv-highgui3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-ml3.2, libopencv-videoio3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-calib3d3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 458158 MD5sum: e72da298725971dee4df68878d0fcd1b SHA1: d4e1f492978cec26a096016f0febe66bc4b16ef8 SHA256: 25e03ed187e13389bd23aada24706ae628a8269fd04ea50d536decc92ace978a SHA512: 92301fd397b7ef52d17b0ec6180ecbafd83b26c7372b41ea39b585d0793d1f566a10ed6a62295aa086b5b34711090cc9ba9d679b5423b1675301c68263a3454e Description: computer vision Camera Calibration library This package contains the OpenCV (Open Computer Vision) Camera Calibration runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-contrib-dev Priority: optional Section: libdevel Installed-Size: 12528 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-contrib3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-flann-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-imgcodecs-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ml-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-photo-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-shape-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-superres-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-video-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-viz-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-contrib-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 1890184 MD5sum: 9d29069941c4f629a445cac51baa5fa1 SHA1: f6fab41706641c6d7fdc70e76d7156c6ef4a52a1 SHA256: b8ecbd56faae865b6b8a1292897b596645d9415f44127b46f0b015276666718b SHA512: 9a7d9097e666e2e48351c95329adcf5fec7d1558246e4e74704f954b417eca6635cf9db06567b68871596d03a88ae8ad95f9a12f1d319c9b5d6b0c2266eacde7 Description: development files for libopencv-contrib3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) contrib library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-contrib3.2 Priority: optional Section: libs Installed-Size: 5232 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-flann3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgcodecs3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-shape3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-superres3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-viz3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:4.0), libgl1-mesa-glx | libgl1, libgl2ps1, libglu1-mesa | libglu1, libhdf5-100, libice6 (>= 1:1.0.0), libjpeg62-turbo (>= 1.3.1), liblept5, libpng16-16 (>= 1.6.2-1), libsm6, libstdc++6 (>= 5.2), libsz2, libtbb2, libtesseract3, libtiff5 (>= 4.0.3), libvtk6.3, libx11-6, libxext6, libxt6, zlib1g (>= 1:1.1.4) Filename: pool/main/o/opencv/libopencv-contrib3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 1486646 MD5sum: 06b69cd79e7a7b6aeff3c7c44138a313 SHA1: a7495e4cf56ba9a928e28e4f73630e91f9d44aec SHA256: d3a3dc4c52454daba591bcab89e91eaf4bcab97342ef1b1021ad7579c43900a0 SHA512: 6494a973b6f433b16232bf76d4f1f9b185eac1e031fc7b0786a1b09f64efdea2a1af68a7a512266d63b62ef58f2aaec1deb5e109704e67c7f0389e2f96a319f4 Description: computer vision contrlib library This package contains the OpenCV (Open Computer Vision) opencv_contrib runtime libraries. This package contain following contrlib libraries: . - aruco - bgsegm - bioinspired - ccalib - dnn - dpm - fuzzy - hdf - line_descriptor - optflow - plot - reg - saliency - stereo - structured_light - rgbd - surface_matching - tracking - datasets - text - face - ximgproc - xobjdetect - xphoto . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-core-dev Priority: optional Section: libdevel Installed-Size: 6568 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libtbb-dev, zlib1g-dev Filename: pool/main/o/opencv/libopencv-core-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 1120136 MD5sum: 65df58fe559b864deacfdce3ad80ae99 SHA1: db96012079d57952e029538310e9325db25c7309 SHA256: 4dd241098c5f61315a349108257ba23fc8af6749f1aaae35ba18e2684bf03b5e SHA512: 36973f4dc3298cfb275da6582eb76b989bd79c23018505fabba2d3a8e18221dfbb2f57bf1d1f790226e297b2ec86fb3d8c54b54a33730b6bdd4640b5253bb12c Description: development files for libopencv-core3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) core. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-core3.2 Priority: optional Section: libs Installed-Size: 2368 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libtbb2, zlib1g (>= 1:1.1.4) Filename: pool/main/o/opencv/libopencv-core3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 737994 MD5sum: a83ed7b09c9db9ecd8df1c0d0c209a54 SHA1: 8a4fa052551af32f7a93dfa5498a5fe18532bf5e SHA256: d6012e35a8f6ac641e522f03bcba156ea9a2e4e9e65b62f1835d4099317212fa SHA512: 3b38fbbf1cb9ed904a76bd1bce0c7be8db4d6aac47723bba184a4c8f0a107aa8382d6b789ddc57647e19b4de6f8cdf27be5d74ac7c32fa650193314a17be4eae Description: computer vision core library This package contains the OpenCV (Open Computer Vision) core runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-dev Priority: optional Section: libdevel Installed-Size: 741 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Replaces: libcv-dev, libcvaux-dev, libhighgui-dev Depends: libopencv-calib3d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-contrib-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-flann-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-imgcodecs-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ml-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-photo-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-shape-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-superres-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ts-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-video-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-viz-dev (= 3.2.0+dfsg-4.1~pn0), libopencv3.2-java (= 3.2.0+dfsg-4.1~pn0), pkg-config, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-calib3d3.2, libopencv-contrib3.2, libopencv-core3.2, libopencv-features2d3.2, libopencv-flann3.2, libopencv-highgui3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-ml3.2, libopencv-objdetect3.2, libopencv-videoio3.2, libstdc++6 (>= 5.2), libtbb2 Recommends: opencv-data Suggests: opencv-doc Conflicts: libcv-dev, libcvaux-dev, libhighgui-dev Breaks: libopencv-core-dev (<= 2.3.1-8) Filename: pool/main/o/opencv/libopencv-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 241340 MD5sum: 43823f5de1ed302c1f65dee57f7819e2 SHA1: baf620c5e8d75194f6c3c1ed99dcc8c4912faddb SHA256: 22a2c647a349cf5e4169cabb7a999c3e7599f0ccd589150e53e767d7a9b4a2d4 SHA512: 2375a7ec114dd5594d580c37de40b8197b184708579bb8103d286151efef48b04b82bb08f021a2c046bb0b063276073d2c79677e204b0531f5ff546b525af85e Description: development files for opencv This is a metapackage providing development package necessary for development of OpenCV (Open Computer Vision). . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: libopencv-features2d-dev Priority: optional Section: libdevel Installed-Size: 1449 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-features2d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-flann-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ml-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-features2d-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 289706 MD5sum: 04d342a2e8fdfaf1a1cbe4389d4e99dc SHA1: fbcd9944943c0de06ec93debe9ab51b6dff06149 SHA256: 3cad4a3ac00eb14006409b1085ef6e9e8f448cd786b7978ebde6b3b1ae9f881e SHA512: 9bff22b321064206db157d6ddb6b064a11e028a1b4dc338342a3588b65262baeb96a67b4c4b11d418c9d25f322ffa644e06b01c3d8c1578eb7e129d7a0301b8f Description: development files for libopencv-features2d3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Feature Detection and Descriptor Extraction library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-features2d3.2 Priority: optional Section: libs Installed-Size: 742 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-flann3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-videoio3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-features2d3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 242144 MD5sum: 98c26bb776c8c39dafb7ea020c91d7ce SHA1: 9977fd81a35ecfeb51c3b8092a8abcdb3565b670 SHA256: fa544dea129e7dce7e814828b1b06989e2379f0fc7359185557325ce2418132d SHA512: 588920ad3d2a2219824e7cff6487aeb1d690f96fc00d0f3c337fb6aa3f9a232cf83875f301228a86a84b5dd842b81e492b5c29ae4483535d5231b844e7e55ee0 Description: computer vision Feature Detection and Descriptor Extraction library This package contains the OpenCV (Open Computer Vision) Feature Detection and Descriptor Extraction runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-flann-dev Priority: optional Section: libdevel Installed-Size: 1393 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-flann3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-flann-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 173268 MD5sum: 2fc0a3594bfb7c0bbcef7e2ac755616a SHA1: a3f5b2c9a2ea4b3a92eefe5e1c32cde902619347 SHA256: 16f8029d33095cb44b59f075bc3de3cc20c7ee623367524c4a398e804cfdd1bb SHA512: e489deef5552e0064aacf8421be898c7765a9a5381dc42a30f84ea0030493a4fcceb534ed2df41cdf78073ad0e3c07966e5b083b0ae8d501e930129e15a0534d Description: development files for libopencv-flann3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Clustering and Search in Multi-Dimensional spaces library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-flann3.2 Priority: optional Section: libs Installed-Size: 346 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libtbb2 Filename: pool/main/o/opencv/libopencv-flann3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 103226 MD5sum: f09295a985122e0218f07b39b6f9f587 SHA1: e94c0ef63495c0b52bd2aa43fa9d03e755f28468 SHA256: 2e8906e5ea7280bb9d6eb40572fe9f6454eb9918334bf1a9dff88d4f934cc26a SHA512: e183a9e39c8600cf8287019922a5d165577937f69eee60192c4688a09a899c57cedb9b0abc84f6daccb1650a50c2e1c4869d5b7a7355474f8a1ddd2cab05530b Description: computer vision Clustering and Search in Multi-Dimensional spaces library This package contains the OpenCV (Open Computer Vision) clustering and search in Multi-Dimensional spaces runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-highgui-dev Priority: optional Section: libdevel Installed-Size: 170 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libavcodec-dev (>= 0.svn20080206), libavformat-dev, libavresample-dev, libdc1394-22-dev, libgphoto2-dev, libjpeg-dev, libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio-dev (= 3.2.0+dfsg-4.1~pn0), libopenexr-dev (>= 1.4.0), libpng-dev, libraw1394-dev, libswscale-dev, libtiff-dev Filename: pool/main/o/opencv/libopencv-highgui-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 43210 MD5sum: 8d461973df91a52b90691be8f60318ca SHA1: 6a880262b0356a72b54a0cb6cbcaf5296e2c1166 SHA256: 202d418478bdbc07ed969223e3fc592d0df67348902d280eeea425a33e1d6aa9 SHA512: 2c082d52079b0e36be7ac61a1a8a7d2d3dd21bb7d2f43b1c4f3ac948edc78945e81eae7b00c53b7369fafe78ba12a7200e92ef0a7695f13d6fe61286513e2033 Description: development files for libopencv-highgui3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) High-level GUI and Media I/O library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-highgui3.2 Priority: optional Section: libs Installed-Size: 78 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0), libatk1.0-0 (>= 1.12.4), libc6 (>= 2.14), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libdc1394-22, libgcc1 (>= 1:3.0), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.31.8), libgphoto2-6 (>= 2.5.10), libgphoto2-port12 (>= 2.5.10), libgtk-3-0 (>= 3.0.0), libopencv-core3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libpango-1.0-0 (>= 1.14.0), libpangocairo-1.0-0 (>= 1.14.0), libstdc++6 (>= 4.1.1), libtbb2 Filename: pool/main/o/opencv/libopencv-highgui3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 31322 MD5sum: 2c78ef63fbf0c7e92a6973783da2b548 SHA1: 2432c7b71196ee3054e951e4315ab2ccd048476b SHA256: f512acfdc3fa4c21f32829d2d0eb5e05282310db2c5ad4e33eba412975c471a3 SHA512: 4594e6d5edd5681d9772667922443866a7ed249859644288da6c98f3dbcec0a0cd05024ca2b3f65548c20d7191f8d46994e90779a8a651453e21f9288fab7743 Description: computer vision High-level GUI and Media I/O library This package contains the OpenCV (Open Computer Vision) High-level GUI and Media I/O runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-imgcodecs-dev Priority: optional Section: libdevel Installed-Size: 747 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libgdcm2-dev, libopencv-imgcodecs3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-imgcodecs-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 121962 MD5sum: 87e8b9cc7b186f4649db73e5e98bfc37 SHA1: c5528b5623ed63ff1ef314ae40357db67d0ab5ee SHA256: e6f52e0c8640ce6adf3717ac182e6b9ca0d53c973a04843dad0c969ae332a70d SHA512: e50aa2b344d0a6b3b9642d109ee345d44bcd1f975a6991a3e04a09bb21c2c8a069001b1b0fb8a56c2085be8e49ffeb11ee46acfee36c28c44a072664bc6e830d Description: development files for libopencv-imgcodecs3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Image Codecs library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-imgcodecs3.2 Priority: optional Section: libs Installed-Size: 234 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), gdal-abi-2-1-2, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libgdal20 (>= 2.0.1), libgdcm2.6, libilmbase12 (>= 2.2.0), libjpeg62-turbo (>= 1.3.1), libopencv-core3.2, libopenexr22, libpng16-16 (>= 1.6.2-1), libstdc++6 (>= 5.2), libtbb2, libtiff5 (>= 4.0.3), libwebp6 (>= 0.5.1), zlib1g (>= 1:1.1.4) Filename: pool/main/o/opencv/libopencv-imgcodecs3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 87838 MD5sum: 46c4efa04a69c1b70762f59a70264c4e SHA1: b3ef20194ed224903e255a533372bfed5e2e08cb SHA256: 9e135538beaa1d7c146a078cdd0d00c99cc473eca9e7f851271d62693bbdaf97 SHA512: cbcb1314e46fc489e204f64cbab545fcb9c8f4b11565be4b236bd82b3601d1c115cefcce5df018e077633912e25d80a573bd0549747fade7768e779950719660 Description: computer vision Image Codecs library This package contains the OpenCV (Open Computer Vision) Image Codecs runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-imgproc-dev Priority: optional Section: libdevel Installed-Size: 5872 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-imgproc-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 1027374 MD5sum: bbbd1d645850bb5a84e6d371471b48bb SHA1: 831c341da321c03f816a026ea8a980031ccf4337 SHA256: c55991e4cb5b3e57d6bc9f28c99c46c0f165171eee84572de00e81b40353ff7e SHA512: 68aff7852dd36498ba03c354a80d63f3e6f80c16de8fc84614b55c87004bbb4014ae7e035dcd6290393ace70150ba6f83c748cbcac9f4a918798e71f3faaad84 Description: development files for libopencv-imgproc3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Image Processing library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-imgproc3.2 Priority: optional Section: libs Installed-Size: 2851 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-imgproc3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 844216 MD5sum: 17dbd1ea63266fc111cff5a0b1acdeee SHA1: c7e9ee46bb61ee595530a35e6cedcbd6b6730341 SHA256: c36331c6e38c1439c540832e19dac693104098687f22c62740aaec8487e3b0fa SHA512: 06ee4872d9a3495461a5ce7dfddbfaa2582fe1543b15b38d7c1e0d9d4498ab77f8e7dbfa59bd3c687ec9cfb4f99a84dfd90985fb531ebe1a9f065b7f1ad228fc Description: computer vision Image Processing library This package contains the OpenCV (Open Computer Vision) Image Processing runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-ml-dev Priority: optional Section: libdevel Installed-Size: 1581 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-ml-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 299888 MD5sum: d2ddef7de55d454eef4da7f1b95006ae SHA1: 8906f0d89bf07e0932b1a6d9c08e3ee5291f24b4 SHA256: ab1473470d3214fd8a55382d7ab4e2777fd478e28a57d7590be6f35c65ec96ba SHA512: c9bc004d55a2b17cd2f394bdec6aa6eeaa2fd69b9076a8beadf283acda7ea4ab27d04658ca51dd6e487e0e665bbfc5c009c0ce054312b61b47459437426dadf3 Description: development files for libopencv-ml3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Machine Learning library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-ml3.2 Priority: optional Section: libs Installed-Size: 710 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), libtbb2 Filename: pool/main/o/opencv/libopencv-ml3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 241940 MD5sum: 4962351802cda1bbbdb9712134b43728 SHA1: 22630b91fd01e105c597a75eda59d5bb60d444f6 SHA256: 4f3345dfef7bb602b7c4af77c5d7d4deb3e3786693252bbbe64bad0e2440e0fa SHA512: 3b3b29ffde82b69dd235968aa2ec22eba734fd53ec00afd2011d10c929b98a7328f5e3211895ae16607be2fe9e1e97c94bd45fb0fb66fa1e255db21da6d82bf3 Description: computer vision Machine Learning library This package contains the OpenCV (Open Computer Vision) Machine Learning runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-objdetect-dev Priority: optional Section: libdevel Installed-Size: 750 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-highgui-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-ml-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-objdetect-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 175078 MD5sum: 58d19663d8f49627d17e1209b032ba02 SHA1: 3a2a56a78c02e6d789f4509b8eddad2936694b27 SHA256: 2b4ed555fe8c8525242d7a96cf810c9a131ae4027bc769c2b7520594011c9189 SHA512: 60da80d20bb494ef38b0674f53315a2c2861b83c73d84b974da7c46ff26831c1e25ecaca4891c96366c6edc33232f32d2edfa144da18b1a74dec48933b4bf602 Description: development files for libopencv-objdetect3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Object Detection library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-objdetect3.2 Priority: optional Section: libs Installed-Size: 374 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-videoio3.2, libstdc++6 (>= 6), libtbb2 Filename: pool/main/o/opencv/libopencv-objdetect3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 151104 MD5sum: add3afe98afece4492b642dc9be9f721 SHA1: bbfdda343f64181c7b6af646ef27a8baed1f15a9 SHA256: 05b4acc81763ea6ef65a947fdc78463c6be824c56e61af589ebf7caad1637aed SHA512: b5822d554a5823a17f52eb47f79c4ba865cc557e7e9130b4b280e4f3cf00e248f1bd2a657d95456747bfe56f13a0271001652718960b7e151bbd4e5e15e9a8ea Description: computer vision Object Detection library This package contains the OpenCV (Open Computer Vision) Object Detection runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-photo-dev Priority: optional Section: libdevel Installed-Size: 1517 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgproc-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-photo-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 232814 MD5sum: 7971c20aef6f4257dc127f04fceca4c0 SHA1: cd7f1ad4f80ff95ecf06e3571a4e508a507330cc SHA256: d19a0dfb585f685ea87a86ebd62ba40c9e8c0628c332544dd1a120d9310e24d5 SHA512: a908071830dce5fc01df68d1552148726824e94890f3c20992b80aab07e7d98260f69865db42e4a6a7e037fc1518422be6dc73e5c880d6c827397531bdd781a5 Description: development files for libopencv-photo3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) computational photography library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-photo3.2 Priority: optional Section: libs Installed-Size: 794 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-photo3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 200288 MD5sum: 3b4e0f0a572c5a6c7654a9ed1c62cb88 SHA1: 7c5759dfba01d1a850fed2f361b7f05a216446d6 SHA256: f79bc57a9db1c617ee6537af652d4dee736d46d6aa1d0e247159aa42799961e1 SHA512: 961236053239d9db4cfa96370bb9f3020405d472eb2b56495bcb01a4b35cebc554ed372f66b59ce0b9fd9b4a84ffa4d6af6bafcb36c339db39b0c64b5ce983ab Description: computer vision computational photography library This package contains the OpenCV (Open Computer Vision) computational photography runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-shape-dev Priority: optional Section: libdevel Installed-Size: 477 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-shape3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-shape-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 82680 MD5sum: b922c62ebcf77cab417c599f81bf1c9a SHA1: e9f1b302cd58516c7881615f5f5eaa2a3d05cd41 SHA256: e612bcc1b3a6483dd386840e3200bed469414ff075764679e3be4eaacbb19e89 SHA512: 0de9fbc27707421efc8a39c5fde44c4a978122b170dd77a0245a4eaa01824c601fba62887251440d9b5397a781d2c18e0719248460d118889c70da0f8f6fd1bf Description: development files for libopencv-shape3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) shape descriptors and matchers library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-shape3.2 Priority: optional Section: libs Installed-Size: 214 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-imgproc3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-shape3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 69280 MD5sum: 876115a6f83979f3a13ab76ca32861c0 SHA1: 542514f4d9de1e658f6457dc3c1a6f0f417e3476 SHA256: 9bf0b7b32c57487680cbf9a114813a60d6b6614e62a9be6ec3876d8e9a3a6c21 SHA512: 69ec7241011b6f407830527e4f2144696c9b3777deff3ba3ceba11463f5d63b0d07fbf4be708e2e1ac9c5a7b22bfb2de51abc0a58224443ced366024001b0abc Description: computer vision shape descriptors and matchers library This package contains the OpenCV (Open Computer Vision) shape descriptors and matchers runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-stitching-dev Priority: optional Section: libdevel Installed-Size: 1240 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-stitching-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 221084 MD5sum: 1287a03990461692c7c571e32ed6ddc2 SHA1: 5523e891a2285044918f4cf8cd6035761d5989fe SHA256: 51f7a7eda47cd0397dc193d7f12c5030659773226a4cbac1e9878e9137c8c954 SHA512: 0507807ced77e9679e5a3239560a2ffb63a0939686532b4de50fead0d26716ff8090a7292470a79f44ac471054656d37cd167e7ee7b63d489d20ccfd9ad810d7 Description: development files for libopencv-stitching3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) image stitching library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-stitching3.2 Priority: optional Section: libs Installed-Size: 554 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-features2d3.2, libopencv-flann3.2, libopencv-highgui3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-ml3.2, libopencv-videoio3.2, libstdc++6 (>= 5.2), libtbb2 Filename: pool/main/o/opencv/libopencv-stitching3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 179674 MD5sum: 9d89fbd8cfc2555674f5b318bf359ad5 SHA1: 5d3f149200a1d248d4b46947173fe7d90c2fc528 SHA256: e9389560c83042c4a4ec97c97e353ab66ed8f048e3983d0dce0ec297c8c08f5f SHA512: 6d27cdacf28449bcef9a26d1b50046e4d2e4079794b6dc16b407cee31001b2366ddcc60844e5b92c7f120e52c123b2b2aef14989f2717f2a247cd60a76d32206 Description: computer vision image stitching library This package contains the OpenCV (Open Computer Vision) image stitching runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-superres-dev Priority: optional Section: libdevel Installed-Size: 332 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-superres3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-superres-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 64062 MD5sum: 36563d72827b826442fc2a49eea17a94 SHA1: e3f4f0f56ee971e9f914c6604a8617befb86de59 SHA256: 49b3187ba7dbc29fc5a3d4f1c54114a47efbfa4ab838918e3725dd57d4fcfb22 SHA512: 73e32aa50170c1a99e5a4c8562f747b08f1ce3bd7ce0fa79d1e3778efc0a08620969c5484e399586b7b8f09e6ba681928a86aa2d1c5b92bbe4b22e3b11a22b7b Description: development files for libopencv-superres3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Super Resolution library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-superres3.2 Priority: optional Section: libs Installed-Size: 174 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.4), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-superres3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 54330 MD5sum: dc2b51045cc0f3670223d2b8e8043007 SHA1: 0b46a774f230522d1f507e5eac43e2a7ab171c20 SHA256: 6844b8c624c499f61a5dd072d56247680b86cdf852a0f5351959c487b80e0926 SHA512: 80b05b89779dba51e60ad0af07fe0c60eb261f1dbbbd4d73f396d5a256bb42ca84289cc64cb88eb03c81841b656b588119af8afd1426382358385ed84a3498cb Description: computer vision Super Resolution library This package contains the OpenCV (Open Computer Vision) Super Resolution runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-ts-dev Priority: optional Section: libdevel Installed-Size: 1628 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-ts-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 281176 MD5sum: ae0098f278c0a3dbe3882347efb5c541 SHA1: 99405a3d27b3d2ee7a8d4ada11ba3b7427fcbaed SHA256: 3f8d187cd0d5f07a8b7230450a4a4a04be14ac63224dc6f24ef77045315b14d3 SHA512: 58808e0f3c0af76c949431a0c3bc1a30035f350adae7c92db639ad8aa07df5cee9f99736d6bdbf3e646b57006e15db3bcac7a209cbbcc3a49e540bcae8216214 Description: development files for TS library of OpenCV (Open Computer Vision) This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) TS library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-video-dev Priority: optional Section: libdevel Installed-Size: 777 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgproc-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-video-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 158940 MD5sum: 1112d1b22713b3ad36733eedcdca39eb SHA1: 8dcd4c76c9442718f59d63429bbd887b93c59b7b SHA256: ba9ad35a9b3f7f7408045260b7b11405b42cfb7019e52095b81d58b7f9b8f676 SHA512: bb83b5b6ff453c1a0ca5c73cd4f1357149a289bbdc189064cc553e0ea9d2f782337825f95fb1bb432d35a980c694267baadea9f7cd6d16d4aeebc21ad43f0c6b Description: development files for libopencv-video3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Video analysis library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-video3.2 Priority: optional Section: libs Installed-Size: 414 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-video3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 132412 MD5sum: 164d8ce6c82e2216063b90d34a162aaa SHA1: 0ee527b367a2ed294656de4fb039dc9edbf4c1f6 SHA256: bdc4cc376c5d9371c345810f318b20c97195021b72e5e02538b97f1c3df26528 SHA512: cd3fad5c38a391685a3e6cdaa4d4d18cdac236813add835bbf1db3f51d54bc01e9241bf2afb4d55c107b84871e0b9370c3e3dc2a5b5e0de654514da6260b03a6 Description: computer vision Video analysis library This package contains the OpenCV (Open Computer Vision) Video analysis runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-videoio-dev Priority: optional Section: libdevel Installed-Size: 608 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libavresample-dev, libgphoto2-dev, libopencv-imgcodecs-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-videoio-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 122390 MD5sum: 2753683a324b92bc39cdbb54b88af964 SHA1: 282de2ced0ef84ab729259303f65713962928298 SHA256: d872d02191e9a77273ee9a8f19cfd896f781ed41f48e02cb608bcb4111bfc0ec SHA512: 5d696be5b8979d1bcab3973da35a27ccb36212ea389a5d974b56a5bc6480170b58fd858a44f076ace8a092a27b9e1a26bbd0620a62e8f83dc75f0c8d922146cf Description: development files for libopencv-videoio3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) Video I/O library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-videoio3.2 Priority: optional Section: libs Installed-Size: 242 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-imgcodecs3.2 (= 3.2.0+dfsg-4.1~pn0), libatk1.0-0 (>= 1.12.4), libavcodec57 (>= 7:3.2.10) | libavcodec-extra57 (>= 7:3.2.10), libavformat57 (>= 7:3.2.10), libavresample3 (>= 7:3.2.10), libavutil55 (>= 7:3.2.10), libc6 (>= 2.15), libcairo-gobject2 (>= 1.10.0), libcairo2 (>= 1.2.4), libdc1394-22, libgcc1 (>= 1:3.0), libgdk-pixbuf2.0-0 (>= 2.22.0), libglib2.0-0 (>= 2.16.0), libgphoto2-6 (>= 2.5.10), libgphoto2-port12 (>= 2.5.10), libgtk-3-0 (>= 3.0.0), libopencv-core3.2, libopencv-imgproc3.2, libpango-1.0-0 (>= 1.14.0), libpangocairo-1.0-0 (>= 1.14.0), libstdc++6 (>= 5.2), libswscale4 (>= 7:3.2.10), libtbb2 Filename: pool/main/o/opencv/libopencv-videoio3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 89476 MD5sum: 5cf74287153c32be33ad7578b0b3eb36 SHA1: c358428c2e664b7fae431d85f9dee5a3e4249a40 SHA256: 0c01665d717755324089dbfbc0ed4bf4100062d92ebaa46d53e30965dc737237 SHA512: 6610b404d9467c4424a6622ce7af4545ef156817b0a1ab664963353d05f2a8125ae824c4fd85e12b7f7d433b4b204d02759862a0b3fa927c8b7c5a3024f52bf3 Description: computer vision Video I/O library This package contains the OpenCV (Open Computer Vision) Video I/O runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv-videostab-dev Priority: optional Section: libdevel Installed-Size: 759 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-photo-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-video-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-videostab-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 129322 MD5sum: 78e9060fafc729c70592db2f3e7ea490 SHA1: a95224c0de01cb35aeadedd380912049fc9deae7 SHA256: ee08cd9ba131baa61b45646b8d2d5a9223b649d139baaab1d842eb10eb5fa1d4 SHA512: 5622f1cf6f3c0367e0bbaa8b01f511be6133fc7a5cc0dad36eb39c4e296faf8dab3368d2e33dbd2ecc30b1835851e686f637e89ca4d0eb30e3c1e198211c15ed Description: development files for libopencv-videostab3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) video stabilization library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-videostab3.2 Priority: optional Section: libs Installed-Size: 354 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-core3.2, libopencv-features2d3.2, libopencv-flann3.2, libopencv-highgui3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-ml3.2, libopencv-videoio3.2, libstdc++6 (>= 5), libtbb2 Filename: pool/main/o/opencv/libopencv-videostab3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 106798 MD5sum: db79907e66bc9e7811c86bc19989c00d SHA1: e0974905a304790d4e0aa6dc6819e3cf6d3970e4 SHA256: d22c76d1780535cf90aa996f8b8c301966779d917ab1a15bf74c041df0b69514 SHA512: 7a278dd04613fb4deade5ef42405e23010e90281b10d36becef0b9b66bf2e0bf190d1d8d240b7d955da9ee8d6f91015a018a8834719c568d723abac079ad07da Description: computer vision video stabilization library This package contains the OpenCV (Open Computer Vision) video stabilization runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-viz-dev Priority: optional Section: libdevel Installed-Size: 1119 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core-dev (= 3.2.0+dfsg-4.1~pn0), libopencv-viz3.2 (= 3.2.0+dfsg-4.1~pn0) Filename: pool/main/o/opencv/libopencv-viz-dev_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 165530 MD5sum: 85258deece55c1a15be015476df6853e SHA1: cd770159926327b8193041ffa0adddc1ed5a2d7b SHA256: bc0432debb38509ade0889b96bf6d600b40cb96999d65ca65e73b096bfbe9266 SHA512: 9f2ac15997dac2a503b049e4c5d674e8692dae546f76a5be8c6b762c3aa35310c42364b44e284c2c19b7419f506fc4f5630048139c6c7722c4c06fc02260c101 Description: development files for libopencv-viz3.2 This package contains the header files and static library needed to compile applications that use OpenCV (Open Computer Vision) 3D data visualization library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Multi-Arch: same Package: libopencv-viz3.2 Priority: optional Section: libs Installed-Size: 402 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-core3.2 (= 3.2.0+dfsg-4.1~pn0), libvtk6.3, libc6 (>= 2.14), libfreetype6 (>= 2.2.1), libgcc1 (>= 1:3.0), libgl1-mesa-glx | libgl1, libgl2ps1, libglu1-mesa | libglu1, libice6 (>= 1:1.0.0), libjpeg62-turbo (>= 1.3.1), libpng16-16 (>= 1.6.2-1), libsm6, libstdc++6 (>= 5), libtbb2, libtiff5 (>= 4.0.3), libx11-6, libxext6, libxt6, zlib1g (>= 1:1.1.4) Filename: pool/main/o/opencv/libopencv-viz3.2_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 127480 MD5sum: 391d7aa327b1fd5815c622c7309e2029 SHA1: 27da1f623ffd12ff337fbf4a9942187ff40f631f SHA256: 0d445c98f030143b83dde9636c8dbe83bc52b949bf6df832f8dc0b392fcaedb5 SHA512: b77668c4e47eee14ef471d09f43d626c88253eede9975e28f40c643918638f038a23f4039be77a21e3d6fb42d237cc7fa831158fbe945e44edaab810eba8ba1d Description: computer vision 3D data visualization library This package contains the OpenCV (Open Computer Vision) 3D data visualization runtime libraries. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Multi-Arch: same Homepage: https://opencv.org Package: libopencv3.2-java Priority: optional Section: java Installed-Size: 438 Maintainer: Debian Science Team Architecture: all Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Replaces: libopencv2.4-java Depends: libopencv3.2-jni (>= 3.2.0+dfsg-4.1~pn0) Breaks: libopencv2.4-java Filename: pool/main/o/opencv/libopencv3.2-java_3.2.0+dfsg-4.1~pn0_all.deb Size: 397784 MD5sum: 50436469ac01cc76a079353d2df062e5 SHA1: 3fc43e3017a99d63aba82bfe067a3a9621dc1366 SHA256: 93c213eee1cccca6e853d1c0ff347067a6adba5776410de08d021fa8397b0329 SHA512: b2a8865710fd10869240645a3aa08ead930d1022a69dbe53757e5b88c2b358d4ec77122b7a4138ffb9eb1de79f68780c9e8977e632f8acc2c7a7c22eddfce126 Description: Java bindings for the computer vision library This package contains Java bindings for the OpenCV (Open Computer Vision) library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: libopencv3.2-jni Priority: optional Section: devel Installed-Size: 953 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-contrib3.2, libopencv-core3.2, libopencv-features2d3.2, libopencv-flann3.2, libopencv-imgcodecs3.2, libopencv-imgproc3.2, libopencv-videoio3.2, libopencv-viz3.2, libstdc++6 (>= 5.2), libtbb2 Filename: pool/main/o/opencv/libopencv3.2-jni_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 199704 MD5sum: ff9c85b21da3abc8214489ea3f2e2978 SHA1: 9b512da8a013e27d8e91baa5eec563a3261db4c4 SHA256: 18f4667ef8303df1b68e553487a3b622a910b295b89d5d1afda0a3bc049b0e26 SHA512: b3a5b8242ec74a4eb4f2bb4d4fb7c59d838f24665855fb0ea903a8d215bb6da8f4f90d9ef88f957dfc756c92bcfca0ad1160bc0c8193775e82ebfe460f365da5 Description: Java jni library for the computer vision library This package contains Java jni library for the OpenCV (Open Computer Vision) library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: libprotobuf-dev Priority: optional Section: libdevel Installed-Size: 9229 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Depends: zlib1g-dev, libprotobuf17 (= 3.6.1-1~pn0), libprotobuf-lite17 (= 3.6.1-1~pn0) Filename: pool/main/p/protobuf/libprotobuf-dev_3.6.1-1~pn0_amd64.deb Size: 1063128 MD5sum: 3460858eb4eaf4953e2624e3c5cbfd56 SHA1: 1c652a4a99a939c878e24445b547910751f55bef SHA256: c28b3edd00ebe109f21c9852fdd96a416c96cdd3ec74a3b140abcf4102826ed8 SHA512: 8a91c1a7ecfafd30f5732b5f00eb2fb1ae2a9023a71d120d99e11906f2dec0d7ece637fee7d966079c7fc874ee3c3d88a6b4baf0ca2750c03a7c4b6d074cd896 Description: protocol buffers C++ library (development files) Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the development headers and static libraries needed for writing C++ applications. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Package: libprotobuf-java Priority: optional Section: java Installed-Size: 786 Maintainer: Laszlo Boszormenyi (GCS) Architecture: all Source: protobuf Version: 3.6.1-1~pn0 Filename: pool/main/p/protobuf/libprotobuf-java_3.6.1-1~pn0_all.deb Size: 712262 MD5sum: f651f749a2095971af80b9529c5a6079 SHA1: 7a1571a43ddf51b2637c59b08efbd52d53899b63 SHA256: d380b3dd2961a4162ff8c3ccee44437369181f375f3f58a839472298fc825d13 SHA512: 09e2ca53fd8bccc89e1873dc72ce99770ca663752caec746f2d822d6d1c001b7b6104d525d86b1a05693111f92f80e5540bdb35839abc8cfe23c4917d1529bcf Description: Java bindings for protocol buffers Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the Java bindings for the protocol buffers. You will need the protoc tool (in the protobuf-compiler package) to compile your definition to Java classes, and then the modules in this package will allow you to use those classes in your programs. Homepage: https://github.com/google/protobuf/ Package: libprotobuf-lite17 Priority: optional Section: libs Installed-Size: 476 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Filename: pool/main/p/protobuf/libprotobuf-lite17_3.6.1-1~pn0_amd64.deb Size: 160058 MD5sum: 239e10481fe338ff59016b95a4d58ec7 SHA1: dc32098a1411b2edb7b9cde927ba6147e8cf4b44 SHA256: fb01e205c07996ae206dc4270f5eabba70d440ca400bf0615b183871485481ff SHA512: 259696429b8f953ff1e53921fe62ea8ceac2ed35bc34e1a333b2dedc8ea8fe9df5fdd5b54bcafdcf6dcad9b5918a5d3e5fdcca356078a0f082b8753f697ef64e Description: protocol buffers C++ library (lite version) Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the runtime library needed for C++ applications whose message definitions have the "lite runtime" optimization setting. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Package: libprotobuf17 Priority: optional Section: libs Installed-Size: 2903 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Filename: pool/main/p/protobuf/libprotobuf17_3.6.1-1~pn0_amd64.deb Size: 778584 MD5sum: 8e41d0121366f565d16b203401875e23 SHA1: c99ca1ed77f3ae861232c441a9feb60de8fe03e3 SHA256: 3fcbeb5405cb14f6c6cbc4b89ce4f3e104de7aba981b5eb9bf617139ae940760 SHA512: 13c2c3cdab13313b7ee072849eab4b70052349df827f4ebbcbead27d1553cbd7a2b73c4268e89165f0629a68b42524d75379f96c67eba6e925d78902a8472ddd Description: protocol buffers C++ library Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the runtime library needed for C++ applications. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Package: libprotoc-dev Priority: optional Section: libdevel Installed-Size: 5383 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Replaces: libprotobuf-dev (<< 2.1.0) Depends: libprotoc17 (= 3.6.1-1~pn0), libprotobuf-dev (= 3.6.1-1~pn0) Breaks: libprotobuf-dev (<< 2.1.0) Filename: pool/main/p/protobuf/libprotoc-dev_3.6.1-1~pn0_amd64.deb Size: 751770 MD5sum: 6b6a0495dacbdb1126adeb81698729ce SHA1: 325d49f6c2439818760da152db1a7f238feb17a5 SHA256: f5b77ec0c3d83f1c9c59f4f306a7eb8ecc190bfb93e401ef8b4fd76532756e0e SHA512: d4f2e96574de18ef741333285edd5c3617ae1a99a5c9e1449ae46a3fe861b563ea8250f17c68a91faf355123887963105e6611383f040b735ddc8e178f57ede0 Description: protocol buffers compiler library (development files) Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the development headers and static library needed for writing protobuf compilers. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Package: libprotoc17 Priority: optional Section: libs Installed-Size: 2493 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Depends: libc6 (>= 2.15), libgcc1 (>= 1:3.0), libprotobuf17, libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Filename: pool/main/p/protobuf/libprotoc17_3.6.1-1~pn0_amd64.deb Size: 669350 MD5sum: 84c4202198bd641051e05cb936a911e2 SHA1: 2c962cac298f4d6988e2863dc86025bba2968ea1 SHA256: 276863379c2610c2b59dd6f77f2e2bbd908f5fc38452d2b8b83e844535033b00 SHA512: 7fa4951bd1e17dc6e41082b85b6af5161bb2c1fd3d7ce5d0c989a3ebbed391d95d619228b52fd961d5e7170cabde448c35e20cf72f7b0beb47cd1f55e2d578e6 Description: protocol buffers compiler library Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the runtime library needed for the protocol buffer compiler. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Package: libwfdb-dev Priority: optional Section: libdevel Installed-Size: 347 Maintainer: Benjamin Moody Architecture: amd64 Source: wfdb Version: 10.5.25~pre2-0~pn1 Depends: libwfdb10 (= 10.5.25~pre2-0~pn1), libc6 (>= 2.3.4) Filename: pool/main/w/wfdb/libwfdb-dev_10.5.25~pre2-0~pn1_amd64.deb Size: 204208 MD5sum: fb542302881fa1d0ab4b6e28dc70086f SHA1: dbf3aceb08548a205c954d1950ffd44b148583d3 SHA256: c5a1c702eba253cc3b650aef24a2d971a980a18fb50e4d959f50e33844421d80 SHA512: 41bf53530be92147947582ee261cf606957a6889399efd037800b116eb987c03537e453578df88512ae5bab4fdb5da61466b3302d86cfa302aad5400d9f11616 Description: WFDB developer's toolkit The WFDB (Waveform Database) library supports creating, reading, and annotating digitized signals in a wide variety of formats. Input can be from local files or directly from web or FTP servers. Although created for use with physiologic signals such as those in PhysioBank (http://www.physionet.org/physiobank/), the WFDB library supports a broad range of general-purpose signal processing applications. . This package includes files needed to develop new WFDB applications in C, C++, and Fortran, examples in C and in Fortran, and miscellaneous documentation. Package: libwfdb10 Priority: optional Section: libs Installed-Size: 146 Maintainer: Benjamin Moody Architecture: amd64 Source: wfdb Version: 10.5.25~pre2-0~pn1 Depends: libc6 (>= 2.14), libcurl3-gnutls (>= 7.16.2) Pre-Depends: multiarch-support Recommends: wfdb Filename: pool/main/w/wfdb/libwfdb10_10.5.25~pre2-0~pn1_amd64.deb Size: 44596 MD5sum: 3cd5aa321a9e88ba5a7b5c3f0c53b3d4 SHA1: 854f54ff2a20237aafd61532775cff32183b7b7d SHA256: 3fb504c3ecef0915429c2650bda7fad32c45641ec445676bfabc4be9220c10b9 SHA512: 887495d6b51545e1899a35a951cf8c8776c95732b1c409f045b9d34cfc2d0895dee35151b54c5b6307b8fc877d94e21b668fdf484f86f8757eb001e92de92df3 Description: Waveform Database library The WFDB (Waveform Database) library supports creating, reading, and annotating digitized signals in a wide variety of formats. Input can be from local files or directly from web or FTP servers. Although created for use with physiologic signals such as those in PhysioBank (http://www.physionet.org/physiobank/), the WFDB library supports a broad range of general-purpose signal processing applications. . This package contains the shared library. Multi-Arch: same Package: opencv-data Priority: optional Section: libdevel Installed-Size: 9848 Maintainer: Debian Science Team Architecture: all Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Breaks: libopencv-dev (<= 2.3.1-12) Filename: pool/main/o/opencv/opencv-data_3.2.0+dfsg-4.1~pn0_all.deb Size: 1205934 MD5sum: c2440176d448effb577e6893da89916d SHA1: 6eafc9224ba1674d41cbe412841dfbebbe0461a1 SHA256: 9057a31ddd9f700cbaab0fb7d977835662ec232723fd24a7b78be3a3866e5d46 SHA512: 012d175364db9cb5bca94291c1221f24c684bfa82b62af774189fc46a9eac26d4657ee0044b9b8703e1a5e15938635c376aa8da206649110452a025f18e5d97c Description: development data for opencv This package contains some architecture independent files useful for development with OpenCV. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: opencv-doc Priority: optional Section: doc Installed-Size: 174183 Maintainer: Debian Science Team Architecture: all Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Replaces: libopencv-doc Depends: libjs-jquery, libjs-mathjax Conflicts: libopencv-doc Filename: pool/main/o/opencv/opencv-doc_3.2.0+dfsg-4.1~pn0_all.deb Size: 59824288 MD5sum: 58492c5ad2f0bedad62b84679c28901d SHA1: b39be2c3a5f7f6359eaee32d8a6d1af6a6d139be SHA256: 6a96c5aea5d2d65b7e0451f130b6a6e9448cc261b80df04431969981efa7e27c SHA512: 85b922ced4729bd03ee1f3f83aa53cc38cdc7b449e9fadf83cd76b79f80829d90848dac9da5463e18225dda0e54823b93532e177400bfc3a84ed79346eb4810e Description: OpenCV documentation and examples This package contains the OpenCV documentation and example programs. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: protobuf-compiler Priority: optional Section: devel Installed-Size: 127 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libprotobuf17, libprotoc17 (= 3.6.1-1~pn0), libstdc++6 (>= 5.2), zlib1g (>= 1:1.1.4) Recommends: libprotobuf-dev Filename: pool/main/p/protobuf/protobuf-compiler_3.6.1-1~pn0_amd64.deb Size: 64654 MD5sum: f41ab33e90f8fb5afdfd3680401daf45 SHA1: 80fdce2cac08bf7d7702ce946acc3422d012babd SHA256: 70a221587c184a4eb1c766af9de5bbb78c8eb366b417428178babab83bf8a5a9 SHA512: f1fd3890a16af104d1300c4a0200c0cd5c668d49937640c8f0a909a41e4f31411b87e170d2f13be4f392f59fa70b0d368a149540e5442e9a0696568ed8bd06ee Description: compiler for protocol buffer definition files Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the protocol buffer compiler that is used for translating from .proto files (containing the definitions) to the language binding for the supported languages. Multi-Arch: foreign Homepage: https://github.com/google/protobuf/ Package: python-absl-py Priority: optional Section: python Installed-Size: 346 Maintainer: Benjamin Moody Architecture: all Source: absl-py Version: 0.2.2-0+pn1 Depends: python-six, python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/a/absl-py/python-absl-py_0.2.2-0+pn1_all.deb Size: 72300 MD5sum: 8107b56b3bd933791fd198468626f562 SHA1: e4bb85e7429935423b61125799290effdeac1c9a SHA256: c8e51d6d960082c3d23b3b0560b7b06faf4505d64fd7843fa41e062a66682fa0 SHA512: 2d103caf1bbd1a4d51cfd6b0d544a31ba3b5da6d45560c9d42f13f5cc004961c86548961325385fcff84b4c48c7dcd5419f513ab95226d37e632abfc081cba57 Description: Abseil Python Common Libraries (Python 2) This repository is a collection of Python library code for building Python applications. . * Simple application startup * Distributed commandline flags system * Custom logging module with additional features * Testing utilities . This package installs the library for Python 2. Package: python-astor Priority: optional Section: python Installed-Size: 95 Maintainer: Debian Python Modules Team Architecture: all Version: 0.7.1-0+pn1 Depends: python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/p/python-astor/python-astor_0.7.1-0+pn1_all.deb Size: 21892 MD5sum: 5c59f142328fd1d8cabf97ea3ee4a248 SHA1: e12808d468dc4ad48e7287448fd2a55d9e7571bf SHA256: bca572f606d9a2d493de25e8e47d8978c0d4636f4192fb61f731ff8c63126cba SHA512: b211920564a2f2d7548457969a57db315589f8a33c16900aaf582fa7d2a8e569131d168c75b65e12ab4cd3c2c6147d43e5f023602b5bb2cffd17d1231d3129b6 Description: Python AST manipulator astor is designed to allow easy manipulation of Python source via the AST. . There are some other similar libraries, but astor focuses on the following areas: . - Round-trip back to Python via Armin Ronacher's codegen.py module: - Modified AST doesn't need linenumbers, ctx, etc. or otherwise be directly compileable . - Dump pretty-printing of AST - Harder to read than round-tripped code, but more accurate to figure out what is going on. - Easier to read than dump from built-in AST module . - Non-recursive treewalk - Sometimes you want a recursive treewalk (and astor supports that, starting at any node on the tree), but sometimes you don't need to do that. astor doesn't require you to explicitly visit sub-nodes unless you want to: - You can add code that executes before a node's children are visited, and/or - You can add code that executes after a node's children are visited, and/or - You can add code that executes and keeps the node's children from being visited (and optionally visit them yourself via a recursive call) - Write functions to access the tree based on object names and/or attribute names - Enjoy easy access to parent node(s) for tree rewriting . This package provides Python 2 module bindings only. Homepage: https://github.com/berkerpeksag/astor/ Package: python-backports.weakref Priority: optional Section: python Installed-Size: 40 Maintainer: Debian Science Maintainers Architecture: all Version: 1.0-2 Depends: python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/p/python-backports.weakref/python-backports.weakref_1.0-2_all.deb Size: 7860 MD5sum: f109fca59030bf6a4136f6a83ac4601a SHA1: c25939d7f6a60d86a76e98003d408332c825c37e SHA256: c24a1b66b29a1b8b7c724068df1ff1c9b4e3569c362fede0c6aa99ed1c9cc6df SHA512: e1db59bc5f46bc7208944caf017bd36469b1526d126c2b6eeeafcedd870ebecfcafb50568c51442c8daaa8c856ee1dc68d80fd6e847a309166a1351957110377 Description: backports of new features in Python 2 weakref module This package provides backports of new features in Python's weakref module under the backports namespace. . This package provides the Python 2 version of the module. Homepage: https://github.com/pjdelport/backports.weakref Package: python-gast Priority: optional Section: python Installed-Size: 46 Maintainer: Benjamin Moody Architecture: all Source: gast Version: 0.2.0-0+pn1 Depends: python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/g/gast/python-gast_0.2.0-0+pn1_all.deb Size: 7054 MD5sum: aea39df69f52c26088574c5c6e34c912 SHA1: 3832925baf30a653e72953121d2acb7614d3e275 SHA256: 01758b89cb35e8439cbfc7c2027b9d535641679b7a8797feea1de0a4a9bd5e52 SHA512: 9aa6f5cea503a19c02d0e41af22809531ab42548ed5647f73325b06651227b9c74cba793ddc31bf88bc7996a8a0b612d244cfaf590608346094e4cf10dd69f15 Description: Generic abstract syntax tree library (Python 2) A generic AST to represent Python2 and Python3's Abstract Syntax Tree (AST). . GAST provides a compatibility layer between the AST of various Python versions, as produced by ``ast.parse`` from the standard ``ast`` module. . This package installs the library for Python 2. Package: python-keras Priority: optional Section: python Installed-Size: 1746 Maintainer: Debian Science Maintainers Architecture: all Source: keras Version: 2.2.2-0+pn1 Depends: python-numpy, python-scipy, python-h5py, python-theano, python-six (>= 1.9.0), python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/k/keras/python-keras_2.2.2-0+pn1_all.deb Size: 228486 MD5sum: 74631e534db6a184e4c5813078805b43 SHA1: 0f4137a440acb2ef90b83b5723479f1cf4dc3f9a SHA256: 2885dd71ac5e9eff21131fb1e6a40ffba46143985fa4eac6e15fc0ff2b5b191b SHA512: 0e83415d5337eef4f487472426a5c16f46abb9fe6433878314897a19fb8db2ef9a865ab6906a09eb8763debb2f1e07195df98253b3b9bb3a9c4420fa3829787c Description: deep learning framework running on Theano or TensorFlow (Python 2) Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation. . Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing). . It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian, but coming up). Homepage: http://keras.io/ Package: python-keras Priority: optional Section: science Installed-Size: 1146 Maintainer: Daniel Stender Architecture: all Source: keras Version: 2.0.2+git20170403+64d24215-0~pn1 Depends: python-numpy, python-scipy, python-h5py, python-six, python-theano, python-yaml, python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/k/keras/python-keras_2.0.2+git20170403+64d24215-0~pn1_all.deb Size: 151218 MD5sum: c76bcff79eb1374236a36d21f54bb756 SHA1: 9ef93168f50d980e3c8fc76102eca460133c5087 SHA256: 86e5ce571ae1524b6cbd8c0a93084776d3edf7c0d93f06f6cc253b856bf97fcc SHA512: ebb00a65d503dd176e18baa2b8a703a664dd7d9b31c4620594dbfc0d656e9a0b50964c66b31f16ec3398184e70ece88a18d11cd82c8b4ca7a6eba8c65c2f541d Description: high-level framework for deep learning (Python 2) Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation. . Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing). . It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian, but coming up). Homepage: http://keras.io/ Package: python-nose-parameterized Priority: optional Section: python Installed-Size: 74 Maintainer: PKG OpenStack Architecture: all Version: 0.6.0-0~pn0 Depends: python (>= 2.7), python (<< 2.8) Pre-Depends: dpkg (>= 1.15.6~) Suggests: python-nose-parameterized-doc Filename: pool/main/p/python-nose-parameterized/python-nose-parameterized_0.6.0-0~pn0_all.deb Size: 11374 MD5sum: df98ae4ae8ad6016f2bab8c0ef00e674 SHA1: 3ae7b9ff8582f373dfc2fcd75fc34137a46eb29b SHA256: 3054901b7a08cf1c9f5c0bde9d4a889a3dba868c08c2ea92fbbde3a7f922d706 SHA512: a4344e0f496b552281e293047e7840f41f550c0338a14fe2e719a3ea9aacd8d4fddc3489d963e6456138e48ba22dcd692cbf3d79e619f478c121833104e87bff Description: decorator for parameterized testing with Nose - Python 2.x nose-parameterized is a decorator for parameterized testing of Python code with nose. . The provided decorators make it simple to pass lists, iterables, tuples or callables to the test functions. This allows you to separate the data from the test without having to subclass unittest.testcase. . This package contains the Python 2.x module. Homepage: https://github.com/wolever/nose-parameterized Package: python-numpy Priority: optional Section: python Installed-Size: 11173 Maintainer: Sandro Tosi Architecture: amd64 Version: 1:1.14.5-1~pn1 Provides: python-f2py, python-numpy-abi9, python-numpy-api12, python-numpy-dev, python2.7-numpy Depends: python (<< 2.8), python (>= 2.7~), python2.7:any, python:any (<< 2.8), python:any (>= 2.7.5-5~), libblas3 | libblas.so.3, libc6 (>= 2.14), liblapack3 | liblapack.so.3 Suggests: gcc (>= 4:4.6.1-5), gfortran, python-dev, python-nose (>= 1.0), python-numpy-dbg, python-numpy-doc Filename: pool/main/p/python-numpy/python-numpy_1.14.5-1~pn1_amd64.deb Size: 2043206 MD5sum: 732682cec42125497365226a499e5627 SHA1: 1d15d467287f22b811b337d6c78d5bad60259203 SHA256: 5ff990c8b93cb66256564f8844c535692e46b4f7c457b51a7c073ea47e1f8d13 SHA512: c91a55716a8cd511d7b22b9c63992a3f8d07dab97b6e27fe96b175c9ac66d89024d42a35e236c0478e521ec7fe5fa0ed36e2c49c714fafc5b5acfb5723473e9f Description: Numerical Python adds a fast array facility to the Python language Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. . Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software. Homepage: http://www.numpy.org/ Package: python-numpy-dbg Priority: optional Section: debug Installed-Size: 26690 Maintainer: Sandro Tosi Architecture: amd64 Source: python-numpy Version: 1:1.14.5-1~pn1 Replaces: python-numpy (<< 1:1.7.1-1) Depends: python-dbg, python-numpy (= 1:1.14.5-1~pn1), libblas3 | libblas.so.3, libc6 (>= 2.14), liblapack3 | liblapack.so.3 Breaks: python-numpy (<< 1:1.7.1-1) Filename: pool/main/p/python-numpy/python-numpy-dbg_1.14.5-1~pn1_amd64.deb Size: 8185408 MD5sum: a274b064e4555a8e155ba57551741a6f SHA1: abf731b14c585f8f50f59a2d30596b9839c8a605 SHA256: d6b5e81c08ccfd61c013a585b0d20ebb272bfbff4d652452a784ad8f23b76935 SHA512: 52ee54678f3951ef52fc918d9fe8a8bd93ac3d3d041d4bb3d69a551b4f1d70b434e3decfa2542ac542dc95ede1c00f7a72a3eee9d50b76d78ac8164a355522a1 Description: Fast array facility to the Python language (debug extension) Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. . Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software. . This package contains the extension built for the Python debug interpreter. Multi-Arch: same Homepage: http://www.numpy.org/ Build-Ids: 0ad156591586729a1eb88993ceb1f1cf14480027 20cd97ee1ea3d72b222eb8260952beef2de0ad08 2c70ebc601a9fa8de3ce7928c6e901aa6cd99ce3 2e7c9ac793e923f2449cf6619a5e35dc3bb554df 441dd8a7401535bd8b52870007fc258d103a1f5e 694591566c826c2e8a8d226de4c72be587958204 6f6576331f6d6dde8a0d7feb70e83c27387a426e 7574923d966bc8d9a487c8103223615633b8a554 7ff213d23db867e5c4eb0510966310ca36c6773f 8f04f469399be3e26fb3e66f6a60a21c6e7a90c9 c523701f370ebf0ea608a4ac86e6df8d604e0643 f64cf85cf4c5ea88bf3880a20c669e0c7cb5efed Package: python-numpy-doc Priority: optional Section: doc Installed-Size: 27819 Maintainer: Sandro Tosi Architecture: all Source: python-numpy Version: 1:1.14.5-1~pn1 Depends: libjs-sphinxdoc (>= 1.0) Filename: pool/main/p/python-numpy/python-numpy-doc_1.14.5-1~pn1_all.deb Size: 3338338 MD5sum: dadf23e0ded184092dbfc576166a2b05 SHA1: 6fd4b76c14896706d9321b6b99d35aa66d17683f SHA256: 0d118adc35646c9bb20afa8949fb5cedc67b8c5a3a6e2467000ed8a12571f3e5 SHA512: 0395d42c679d2afe4085e7618b62844c5caad5bf0bbe3a152a6b2260954c01274ccf9f33e467c6b33af63853354c47ed5b280c7ba5faa48f8a812e21cffd5a43 Description: NumPy documentation Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. . Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software. . This package contains documentation for Numpy and f2py. Homepage: http://www.numpy.org/ Multi-Arch: foreign Package: python-opencv Priority: optional Section: python Installed-Size: 2915 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-flann3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgcodecs3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-shape3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-superres3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-viz3.2 (= 3.2.0+dfsg-4.1~pn0), python (<< 2.8), python (>= 2.7~), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python:any (<< 2.8), python:any (>= 2.7~), libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-contrib3.2, libopencv-core3.2, libstdc++6 (>= 5.2) Filename: pool/main/o/opencv/python-opencv_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 546758 MD5sum: 1876fcb60a69b8c5fa7d7926627cb327 SHA1: 7ddbde41e5519ed35d360f1c00bd1601b7ac736f SHA256: 42846dde88853eb9e77ea3988cca930e1affb99dc968258a9b0cede38cf1937b SHA512: 6d1b0447295b35d8f33194500e7cb79cbbca9e363b85d605cad9ccd9e37fd83cab5fb80706726c4ac7cc2beedcb4a171ed4b89874f992c54948b4f2895401a53 Description: Python bindings for the computer vision library This package contains Python bindings for the OpenCV (Open Computer Vision) library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: python-protobuf Priority: optional Section: python Installed-Size: 2738 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Provides: python2.7-protobuf Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libprotobuf17, libstdc++6 (>= 5.2), python (<< 2.8), python (>= 2.7~), python-pkg-resources, python-six (>= 1.9), python:any (<< 2.8), python:any (>= 2.7.5-5~) Filename: pool/main/p/protobuf/python-protobuf_3.6.1-1~pn0_amd64.deb Size: 331718 MD5sum: 0bb39d9c4f7e62eea60cac17878428da SHA1: f4cbb6d1af3cdfa86f437659b2e5c92497477c64 SHA256: 0f0ab601f875fbe3895a643c3cf9ff748c543f1d683eb61450fb6e2e20792ced SHA512: fe4f81ee4be842af704df4b49368f2284d96ecbd5dc10b822f31a1a94aecb6cdb4eff40ffe683a1701b839118969eb170b1c3b3e1f6f3cd143cffbdc947a44e0 Description: Python bindings for protocol buffers Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the Python bindings for the protocol buffers. You will need the protoc tool (in the protobuf-compiler package) to compile your definition to Python classes, and then the modules in this package will allow you to use those classes in your programs. Python-Version: 2.7 Homepage: https://github.com/google/protobuf/ Package: python-scipy Priority: optional Section: python Installed-Size: 42221 Maintainer: Debian Python Modules Team Architecture: amd64 Version: 1.1.0-1~pn0 Provides: python2.7-scipy Depends: python-decorator, python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python (<< 2.8), python (>= 2.7~), python:any (<< 2.8), python:any (>= 2.7.5-5~), libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, libquadmath0 (>= 4.6), libstdc++6 (>= 5.2) Recommends: g++ | c++-compiler, python-dev, python-pil Suggests: python-scipy-doc Filename: pool/main/p/python-scipy/python-scipy_1.1.0-1~pn0_amd64.deb Size: 10137004 MD5sum: 1a8818b16909acd24061cd8ad4d86553 SHA1: 10178d6bec008c7a77b0dfad842ea0644769a82f SHA256: 19cb562182fe383255bb053934dcb606a487066d1483937d174104a82c14a587 SHA512: b72809a9f13020d83a3f170277623113e6b73baeaa26d78717d5181963501cd4b1b7f217d67e2cff29410993884fa7068cfffd545bd069b3ab7c6d5e5fb13229 Description: scientific tools for Python SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package. . SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. Homepage: http://www.scipy.org/ Package: python-scipy-dbg Priority: optional Section: debug Installed-Size: 86776 Maintainer: Debian Python Modules Team Architecture: amd64 Source: python-scipy Version: 1.1.0-1~pn0 Depends: python-dbg (<< 2.8), python-numpy-dbg (>= 1:1.5.1), python-scipy (= 1.1.0-1~pn0), python-numpy (>= 1:1.10.0~b1), python-numpy-abi9, python-dbg (>= 2.7~), python-dbg:any (<< 2.8), python-dbg:any (>= 2.7~), libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, libquadmath0 (>= 4.6), libstdc++6 (>= 5.2) Filename: pool/main/p/python-scipy/python-scipy-dbg_1.1.0-1~pn0_amd64.deb Size: 32068598 MD5sum: 374b8e6871e8610d230286cc20325638 SHA1: 7d2ec814a1bdf24aa6423d18c1df899e8a72024b SHA256: 19a99e20a2eab970718a6052293cbd3bbe05da730c87815d355272269009b2c5 SHA512: ff42f74202c240185ff3d5e079d06db3f7c6e65bee5e0fe3539dd1ff4540b1d61901b2e02dae4f57bd6527c759b4d674aa983d369b0363903fca852ddbe0052e Description: scientific tools for Python - debugging symbols SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package. . SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. . This package provides debugging symbols for python-scipy. Build-Ids: 05df30244c65ea34ea9d50d812550990acb07ba7 08c565ae8a73bf09e7edbdb2f22eb22a061297a4 0aaa17d73fdf6dea65af8879e31e57cbb35788a6 0dfc3b1dd68f24bec96dd54b241cd33ba2dbb419 11362ddc624140f7c3455f5db7c14eb8c406bd6c 1387c05805405a6812d011b9ce057638ff3a1b5e 16578a3f3e472e8875a8f4f0d10f93e59923b31d 18ee808f3a35357e3125a8fa1eff7a1ec6acbef3 19c9d510cb8b9b3af3c55b7e312df9892183b375 1f667b9119b2a24b835a4e3e478afbf42494e60a 20335dd1d664ffe73bd0e57ad47affa2c8c200d2 269237ae275f759d6d79da39e5acba5b000204ff 283350b5a005f745dd0b8aa02620a51d0c202a52 2dbf37d1d7dcff8a2931de2ecb78abfae146a872 30122f37c7b4985c6efdc74002d71af458e9f7a0 30c35b019528eb2fae24f5d8c9c8d8c821d6ef0f 3176528878b43cf3f36b92ef919ee50f32ab8b72 3490f4d8610feae4c600608786c5c1d169376321 3987f0eb14405d6a5d3f9ab43ad219a0e7a13d39 39ff2224a0540761f50dc9a180bce3014016af48 4292b1fd238f787eabc7dd5ccc4e79c5f67c5a84 44362c225e14b478b0f232313afc5fc945aa8c88 466ac40d54edd35ca0cfd676f54d28fe5f57a0f9 49028fdc7daa7a6da09936418c8a93d632efcf9a 4d5c30430b41ff208bf9a132d863f84dc7678edd 4ed1ccc4930a7572a86ff2327c317422c791454d 511011194dfe758b52b5b74fc9d015fb75fc2236 54c02ab655361857c5350088ee714b2b63e3de5b 5557667ab5fb8bb5756cd5bab7402cfb543faec7 55bb33d815683d0a1ef660d2f5567b443d2388ed 56c2c39106d1d73830a7225bfc77096a8877d984 5776b88799a479708541b284808d21302df7550c 57b47170b5cd46122806f5af95c819fa8fe099af 5ba5e609f8c8729bffe3dc0a309e31e8848a82e2 5f611627e2d58784ad8b68982141161e7c641edc 654aaf459a0882c340d959cbe400616413036336 665777e6c21165fec80c19a2c8a12c3899aafdb0 6909f365f004fbd8a171b44c51c22b4cfa80a509 698083abaacbd706a05c7d8e807415f501b9f814 6c36504b1ea2a5c45c3a6a76cbe46bb92c3bdcc5 6d814941233b026836e3b4b088b93225dcbd0bf5 6ef2273d216842e4d1939d749e1888690779aece 6fa427fbab562a2f426bb0eb91841b84f85d98a2 73416e7ce8a0840d620a16b05af4870f408f9549 78979540ea00227722045db6b0da636c058aaff7 797104414b550ec9d624c49398dfc7257cbc7b5b 7d0935a5715c1024ed8b17b76c5613b3847ced35 8373c6ca2b06f068a958b722aabcbb0c17afae93 88dab9fe49ba4a3d8233ab2419f377a8606d26d3 9131c0b88e5cddcaa3ebdf2a61ef0f1d4e07d82c 93deb29336b49856a12a437d94a392a31652f05d 990f62177ff01c98a06d0ff830b1fb7f294c60dd 9eabb128103a27a2a67c441341a136cac175bb98 a4d422899077341fb801a4dc800d2406726a7c5f af4916d1fb7a2af0e01466240b2619185e53f3b3 b0e977e0fa0bedf95eced025fdbcce02f9f2d23b b24f0f4edcda474cc549dd7cd7204c56f819a35d b3070ebbe4c5355b9b52edd8ca644f9df06cef0b b6d3f75575203893f2622b6b70819148b1891be1 bae9d6d0eeaa454cb8faf5a8f3f5bb2a9f2e407f c4ac54ff7fa9fcd3b24cbec77589e477ae6dc66b c996c3798ed51b540d551dbcb8edda222d0247d5 cceaafb26422c8a29244da2d34255bb783f10d74 ce91bb385bb71f95fc825016334eea962656f82b d361e2c6f0e30a6a19d28095e544e64cb0332c74 d4df72310dd98ace5ba13464e2618836da0e46b1 d6385f5d69c682cc6474d3df4b449a2588f701ad d8b78d42cded0b9a4fbefb2c03d5d198d262e9e5 daa4c0fca26078363011c7a625ffbb2cbe6e79b7 dbfc97a5c389cde48915019bfd25feacf1b668d3 dfd59e18f5c7e8556c2ee6fae0c7872f3a69b799 e039ed09222af870bfc6b2ca30e9ab7a163109fc ea80113631625f8ca27cb381c00815728cdf1598 ee4ac8aec187f1458274f735bd4f844c0b43d641 f1aff080296f3180ccc3a7b6637c292e18335a2b f47f9b31dc3ec3cf80847db6ab3455674f3ed9b9 f646f57e25471aff29bf333faf21cf7b37071657 f68ac624acddfe2a8fb450c95ea5e4b803d19b70 fc9be8f57a853e15abc51d7794df3a198babb5e0 fd6dc56f57ee12aa4d42a18e63710c95724a1761 fe531d63ba6311cd7ae63d88707f9dd7b9f98edc fe779540db9f00a2a95ad14ef1c4823ea366b300 Homepage: http://www.scipy.org/ Package: python-theano Priority: optional Section: python Installed-Size: 12261 Maintainer: Debian Science Maintainers Architecture: amd64 Source: theano Version: 0.9.0-0~pn1 Depends: python-numpy, python-scipy, python-six (>= 1.9.0), python:any (<< 2.8), python:any (>= 2.7.5-5~), python-dev, libblas-dev | libblas.so Recommends: python-pydot, python-nose, python-nose-parameterized, theano-doc Suggests: nvidia-cuda-toolkit, python-pycuda Filename: pool/main/t/theano/python-theano_0.9.0-0~pn1_amd64.deb Size: 2094604 MD5sum: 131c2342a777feaf427f2b0b1b554360 SHA1: e40e375ee8c00bc3e307a2808373a1baf011ae9d SHA256: 87c5a7c55d78955022140e1a569ff9299208202eb0aa8eafc5e8ef896d55e220 SHA512: 4306650fe84b29996139016a1339e5545e6e67573aa61b81e07d1eae8cfe4a7fa1df6c9e2151153c6c2e37fa653a9e2e9a4383d8e1e331e819256f3ef7c53484 Description: CPU/GPU math expression compiler for Python Theano is a Python library that allows one to define and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It provides a high-level Numpy like expression language for functional description of calculation, rearranges expressions for speed and stability, and generates native machine instructions for fast calculation. Optionally, highly accelerated computations could be carried out on graphics cards processors. . This package contains Theano for Python 2. Homepage: http://www.deeplearning.net/software/theano/ Package: python-xgboost Priority: optional Section: python Installed-Size: 3956 Maintainer: Benjamin Moody Architecture: amd64 Source: xgboost Version: 0.6+git20160810-0~pn1 Depends: python (<< 2.8), python (>= 2.7~), python-numpy, python-scipy, python:any (>= 2.7.5-5~), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.9), libstdc++6 (>= 4.9) Filename: pool/main/x/xgboost/python-xgboost_0.6+git20160810-0~pn1_amd64.deb Size: 926358 MD5sum: 48605d05d0584c264fb72814e7fb8aee SHA1: ed267f9bc6a1dd9b789162c07d05bd314032597f SHA256: 50992a768661cc77dd241edc07b4ad555302ceb82508617f01fe00f012357be2 SHA512: 44bb36b5ae77fdfb452b043f1461ed5c063df352122a626feb6cbe9e1bb35ef49a04229d0aa8994d7be7b1cc6cef224d6a115862f97d4370aaeb20f69eac049d Description: scalable, distributed gradient boosting library (Python 2) XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples. . This package provides the xgboost library for Python 2. Package: python3-absl-py Priority: optional Section: python Installed-Size: 346 Maintainer: Benjamin Moody Architecture: all Source: absl-py Version: 0.2.2-0+pn1 Depends: python3-six, python3:any (>= 3.3.2-2~) Filename: pool/main/a/absl-py/python3-absl-py_0.2.2-0+pn1_all.deb Size: 72354 MD5sum: dbcaabfd261ec1753c04fcd9a94b8296 SHA1: c9b359777e0e87f499ea4dfe53e059073f912226 SHA256: c2f30eb9bca5b0ddfc075bd9895a4242c7e895867bb35e4b3c19017c5bd74482 SHA512: ff7346da0be9df11bc0fbb1950bda5c05b9c9012db89d2e8b20a78eade2aece25cf6890e48f29be82ff7b8549cbbe250fd5e9b6dd3946148cb869cf4f9fdefbe Description: Abseil Python Common Libraries (Python 3) This repository is a collection of Python library code for building Python applications. . * Simple application startup * Distributed commandline flags system * Custom logging module with additional features * Testing utilities . This package installs the library for Python 3. Package: python3-astor Priority: optional Section: python Installed-Size: 95 Maintainer: Debian Python Modules Team Architecture: all Source: python-astor Version: 0.7.1-0+pn1 Depends: python3:any (>= 3.3.2-2~) Filename: pool/main/p/python-astor/python3-astor_0.7.1-0+pn1_all.deb Size: 21960 MD5sum: 4ce96a50562330f0f54a94bf50357470 SHA1: 7f68da7bb2332bb950794cd6e4acc435b190dc44 SHA256: 438f6d579154fe582a83c59962b617f1d909c4adc52d2a12c599d05d1ac67bbc SHA512: 05c18c01372f4fff2e3aab46dd64da12e845a4b0706bdea78141f2b547347fc151b7e93dba865ca7b8a2f87d23a61d0e8bf466d1c29134b2751a7a729217a0f4 Description: Python 3 AST manipulator astor is designed to allow easy manipulation of Python source via the AST. . There are some other similar libraries, but astor focuses on the following areas: . - Round-trip back to Python via Armin Ronacher's codegen.py module: - Modified AST doesn't need linenumbers, ctx, etc. or otherwise be directly compileable . - Dump pretty-printing of AST - Harder to read than round-tripped code, but more accurate to figure out what is going on. - Easier to read than dump from built-in AST module . - Non-recursive treewalk - Sometimes you want a recursive treewalk (and astor supports that, starting at any node on the tree), but sometimes you don't need to do that. astor doesn't require you to explicitly visit sub-nodes unless you want to: - You can add code that executes before a node's children are visited, and/or - You can add code that executes after a node's children are visited, and/or - You can add code that executes and keeps the node's children from being visited (and optionally visit them yourself via a recursive call) - Write functions to access the tree based on object names and/or attribute names - Enjoy easy access to parent node(s) for tree rewriting . This package provides Python 3 module bindings only. Homepage: https://github.com/berkerpeksag/astor/ Package: python3-backports.weakref Priority: optional Section: python Installed-Size: 37 Maintainer: Debian Science Maintainers Architecture: all Source: python-backports.weakref Version: 1.0-2 Depends: python3:any (>= 3.3.2-2~) Filename: pool/main/p/python-backports.weakref/python3-backports.weakref_1.0-2_all.deb Size: 7868 MD5sum: 758c91fdc6a27f7a1056fc96f6ef7d48 SHA1: 07986af43a195d4a5a5e7d0974181dfe14c120fd SHA256: 19baa9b81ab14070b8aebdfb9e6399b732ddc977a732fe2338c084e4555f2f38 SHA512: 934630c359ec0e56fae0f9affd900f7c67822fc48d1bd10165193bb2546889a5a67ea0e3148711726d935676bc11ee474090b0d33b9c5dbd2710ca8f2da14ad7 Description: backports of new features in Python 3 weakref module This package provides backports of new features in Python's weakref module under the backports namespace. . This package provides the Python 3 version of the module. Homepage: https://github.com/pjdelport/backports.weakref Package: python3-gast Priority: optional Section: python Installed-Size: 46 Maintainer: Benjamin Moody Architecture: all Source: gast Version: 0.2.0-0+pn1 Depends: python3:any (>= 3.3.2-2~) Filename: pool/main/g/gast/python3-gast_0.2.0-0+pn1_all.deb Size: 7120 MD5sum: 0ac2e222ba31407d3f4bce20619cfc72 SHA1: c38ba86fe56cc9d62ec0eb6aa481a617ab6a37f5 SHA256: fd6b3b2fd98f1e1ccc7e7a73006b21dd3e4d39349b5cfb4445939d54d5feed96 SHA512: 43d4401cb7728d622c88014a7053579da4e924c1e7ef32754847b330cb3880c86a91155075ea86687e8c20512826376b5d838c945d3c48093a1221066756bd9d Description: Generic abstract syntax tree library (Python 3) A generic AST to represent Python2 and Python3's Abstract Syntax Tree (AST). . GAST provides a compatibility layer between the AST of various Python versions, as produced by ``ast.parse`` from the standard ``ast`` module. . This package installs the library for Python 3. Package: python3-keras Priority: optional Section: python Installed-Size: 1746 Maintainer: Debian Science Maintainers Architecture: all Source: keras Version: 2.2.2-0+pn1 Depends: python3-numpy, python3-scipy, python3-h5py, python3-theano, python3-six (>= 1.9.0), python3-yaml, python3:any (>= 3.5~) Filename: pool/main/k/keras/python3-keras_2.2.2-0+pn1_all.deb Size: 228528 MD5sum: 85283fe3bd00057ebe584bde532aab05 SHA1: e1de11c6b7b57b8737c6b8c5ba24ede48ae0327d SHA256: 68e60d30eb11a46b654fc4c1be604eae6c52a7ee8d6cf8268ff87ec32766dfc4 SHA512: a6972903fcacb36b6e481c6a36cfb78e30210e267e67720e8932add8d82c9d0856ed6157faeb36ab474fd9aa280f6b30f3cb23527bf2a4274b491a0d66a7e1f7 Description: deep learning framework running on Theano or TensorFlow (Python 3) Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation. . Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing). . It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian, but coming up). Homepage: http://keras.io/ Package: python3-keras Priority: optional Section: science Installed-Size: 1342 Maintainer: Daniel Stender Architecture: all Source: keras Version: 2.0.2+git20170403+64d24215-0~pn1 Depends: python3-numpy, python3-scipy, python3-h5py, python3-six, python3-theano, python3-yaml, python3:any (>= 3.3.2-2~) Filename: pool/main/k/keras/python3-keras_2.0.2+git20170403+64d24215-0~pn1_all.deb Size: 195526 MD5sum: 6099b56ff5b9a9a6b018f8bb315f24d9 SHA1: 3b84533864e125f919d65e0afe7d8aab6aab56b7 SHA256: 73b9336ab3f76babad36848829045c3bd33c833d146d57bfc1d6fe51fb4ff920 SHA512: b6df263592e3041a2ead19c3ff4ad4a1ff1cb86cb9a5d40fb313119341a7760422fb4263ef1fd60e09af2ced7619f52bf06d0dfe0267d0a7f9b6f9231e9af98b Description: high-level framework for deep learning (Python 3) Keras is a Python library for machine learning based on deep (multi- layered) artificial neural networks (DNN), which follows a minimalistic and modular design with a focus on fast experimentation. . Features of DNNs like neural layers, cost functions, optimizers, initialization schemes, activation functions and regularization schemes are available in Keras a standalone modules which can be plugged together as wanted to create sequence models or more complex architectures. Keras supports convolutions neural networks (CNN, used for image recognition resp. classification) and recurrent neural networks (RNN, suitable for sequence analysis like in natural language processing). . It runs as an abstraction layer on the top of Theano (math expression compiler) by default, which makes it possible to accelerate the computations by using (GP)GPU devices. Alternatively, Keras could run on Google's TensorFlow (not yet available in Debian, but coming up). Homepage: http://keras.io/ Package: python3-nose-parameterized Priority: optional Section: python Installed-Size: 73 Maintainer: PKG OpenStack Architecture: all Source: python-nose-parameterized Version: 0.6.0-0~pn0 Depends: python3:any (>= 3.3.2-2~) Pre-Depends: dpkg (>= 1.15.6~) Suggests: python-nose-parameterized-doc Filename: pool/main/p/python-nose-parameterized/python3-nose-parameterized_0.6.0-0~pn0_all.deb Size: 11282 MD5sum: 3e044b2eb30931cbadd1bd8bc19bc49f SHA1: c1068539b58bf40579c5e0dc24cd87cfbbc704c6 SHA256: fd95bc8edc92cc4d92e1f0ef6a53c7b1112846371967ae21b3570f3a37d6f822 SHA512: 3c488a46d8a568bdf5f4ee404d654bea7917fa4457ecbb6754550abbe92226564f218a98bb4c7057d3de9b2012c92f3eec6f33231494197b04370ac72052412e Description: Decorator for parameterized testing with Nose - Python 3.x nose-parameterized is a decorator for parameterized testing of Python code with nose. . The provided decorators make it simple to pass lists, iterables, tuples or callables to the test functions. This allows you to separate the data from the test without having to subclass unittest.testcase. . This package contains the Python 3.x module. Homepage: https://github.com/wolever/nose-parameterized Package: python3-numpy Priority: optional Section: python Installed-Size: 11139 Maintainer: Sandro Tosi Architecture: amd64 Source: python-numpy Version: 1:1.14.5-1~pn1 Provides: python3-f2py, python3-numpy-abi9, python3-numpy-api12, python3-numpy-dev, python3.5-numpy Depends: python3 (<< 3.6), python3 (>= 3.5~), python3.5:any, python3:any (>= 3.3.2-2~), libblas3 | libblas.so.3, libc6 (>= 2.14), liblapack3 | liblapack.so.3 Suggests: gcc (>= 4:4.6.1-5), gfortran, python-numpy-doc, python3-dev, python3-nose (>= 1.0), python3-numpy-dbg Filename: pool/main/p/python-numpy/python3-numpy_1.14.5-1~pn1_amd64.deb Size: 2040516 MD5sum: d560c2d7025388122f44b774d8ab436e SHA1: 691eb954dbec5126863d51070fd8f08ee313580c SHA256: 625acf6572cac2f5c330b08694aab6cdf7fc62084c23c6f273deb54304e7f6f3 SHA512: a3ce866281426d5541c6c4b4a2a59d0314c7b0f99684f4bb8a26f14673082100989fdbcba4500f194ca7f4ce908bd4e5728eb28732fc3724d099ddfc361e4a82 Description: Fast array facility to the Python 3 language Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. . Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software. . This package contains Numpy for Python 3. Homepage: http://www.numpy.org/ Package: python3-numpy-dbg Priority: optional Section: debug Installed-Size: 33661 Maintainer: Sandro Tosi Architecture: amd64 Source: python-numpy Version: 1:1.14.5-1~pn1 Replaces: python3-numpy (<< 1:1.7.1-1) Depends: python3-dbg, python3-numpy (= 1:1.14.5-1~pn1), libblas3 | libblas.so.3, libc6 (>= 2.14), liblapack3 | liblapack.so.3 Breaks: python3-numpy (<< 1:1.7.1-1) Filename: pool/main/p/python-numpy/python3-numpy-dbg_1.14.5-1~pn1_amd64.deb Size: 13399660 MD5sum: 456791cceb68ee0982d023b4a343138a SHA1: 5bc61ead25f0f118f116363ce8d4a11956303883 SHA256: f7dd357aaee2123930e15ae7f3e3ceba37994f16ec5d66614de0744a78ae7a2a SHA512: b8f06ece6b8df1e504a95f4e8430ad7e1a1ac3ec1f9e00149cf7f8789d5373f23eddbc8ccf5c0587eefe96efc2c35ad9e14a360bf7a003634a50fe29964a34b2 Description: Fast array facility to the Python 3 language (debug extension) Numpy contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, and useful linear algebra, Fourier transform, and random number capabilities. . Numpy replaces the python-numeric and python-numarray modules which are now deprecated and shouldn't be used except to support older software. . This package contains the extension built for the Python 3 debug interpreter. Multi-Arch: same Build-Ids: 0f7525dbf9576c2c061c915519534ee3b1c1b400 25e2fdcc24cce1131ea3c3767ebde3afb8ad9dd8 2b08b2035142eff54a04b966dce680d54d44525a 2baec013ed8384e6ccc94543516828b4161a3fcb 3a16bc3077530d1f56ffa03855a35038441c7f77 3f092c11feef7c172ccf05495caeb3c04b3f6b1b 592a46554bda5431a11cdc779717d3b83148892d 5fda49e9f91a2372061eeef3e8222ea82a17b552 6446ab3d6756a0af6647fe21b0116c0b6d010df9 6b1df0f918b107f3debd5f7f662fbd0a27090b9b 70ef3f48bf70b90857473066e511183429fa5b34 7e50afd3787bc20f9e6a54d52b011b925e967161 86529f675ca2256d3278e8976b4b085379ae9805 98265089110157dcba3f54f31311d05c25a77a16 9bc1e3b7789b0ad2b46b8a91c284d1e77704252e a0f992b21fb515e7f7c75d2b82da348307a18e2a bff2c657be2beb4831dfa9ca7d32be40a78ee1e5 cb6bc1be428b15fc94a43d4d473356112e3f6b98 d1c1cd8c55d22fab8be081ab02e2f6c69ba5aeb4 d5cbc7f7a959aa4af7b073e6c4211a9e74d98555 d8039786c61d3b9775fe22c949d6546b063198c6 eb041cd290b9ca3f8d9ec9a39612afef4bf09fd2 f9156caa185aa8b414ed41f19f63edd290c65a44 fb9f564d3a588e5d527909622121cb467a7ad42a Homepage: http://www.numpy.org/ Package: python3-opencv Priority: optional Section: python Installed-Size: 2913 Maintainer: Debian Science Team Architecture: amd64 Source: opencv Version: 3.2.0+dfsg-4.1~pn0 Depends: libopencv-calib3d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-features2d3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-flann3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-highgui3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgcodecs3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-imgproc3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-ml3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-objdetect3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-photo3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-shape3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-stitching3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-superres3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-video3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videoio3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-videostab3.2 (= 3.2.0+dfsg-4.1~pn0), libopencv-viz3.2 (= 3.2.0+dfsg-4.1~pn0), python3 (<< 3.6), python3 (>= 3.5~), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, libc6 (>= 2.14), libgcc1 (>= 1:3.0), libopencv-contrib3.2, libopencv-core3.2, libstdc++6 (>= 5.2) Filename: pool/main/o/opencv/python3-opencv_3.2.0+dfsg-4.1~pn0_amd64.deb Size: 545264 MD5sum: 92114cc7b007b3cbd7db148543423a0f SHA1: da93d5c1244ae22755b106546816363326e74fc9 SHA256: 9c371fdc574b2136521ae9ba7183a53f19ca95da3a4e8a8eeec60303c98fedd6 SHA512: 1ae38cbf534d0099ed02ec9093a7f3259971853d9aa805fc23cdaaea53fc0224c86379256c032363b4d6c15583f5758e03db08a6ddee2d7e2ce8b4b1b5833690 Description: Python 3 bindings for the computer vision library This package contains Python 3 bindings for the OpenCV (Open Computer Vision) library. . The Open Computer Vision Library is a collection of algorithms and sample code for various computer vision problems. The library is compatible with IPL (Intel's Image Processing Library) and, if available, can use IPP (Intel's Integrated Performance Primitives) for better performance. . OpenCV provides low level portable data types and operators, and a set of high level functionalities for video acquisition, image processing and analysis, structural analysis, motion analysis and object tracking, object recognition, camera calibration and 3D reconstruction. Homepage: https://opencv.org Package: python3-protobuf Priority: optional Section: python Installed-Size: 2733 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Provides: python3.5-protobuf Depends: libc6 (>= 2.14), libgcc1 (>= 1:3.0), libprotobuf17, libstdc++6 (>= 5.2), python3 (<< 3.6), python3 (>= 3.5~), python3-pkg-resources, python3-six (>= 1.9), python3:any (>= 3.3.2-2~) Filename: pool/main/p/protobuf/python3-protobuf_3.6.1-1~pn0_amd64.deb Size: 331500 MD5sum: 6862f89d5e6b33c2902fa8075d278149 SHA1: 60e124d471e9545aacc4f71f3dc7aaee82d9b184 SHA256: 216d1fb620b25370e98b95b533f8a7a81a81bfeda847470bb3015c3825e05f21 SHA512: a5d648463c342029c28c23e6282958baf29da7e1809e7645ea856951e5374dd2ac00ddce3be34ff5142a82a866387e6638c379a788084c956f6743f178ded23d Description: Python 3 bindings for protocol buffers Protocol buffers are a flexible, efficient, automated mechanism for serializing structured data - similar to XML, but smaller, faster, and simpler. You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. You can even update your data structure without breaking deployed programs that are compiled against the "old" format. . Google uses Protocol Buffers for almost all of its internal RPC protocols and file formats. . This package contains the Python 3 bindings for the protocol buffers. You will need the protoc tool (in the protobuf-compiler package) to compile your definition to Python classes, and then the modules in this package will allow you to use those classes in your programs. Homepage: https://github.com/google/protobuf/ Python-Version: 3.5 Package: python3-scipy Priority: optional Section: python Installed-Size: 41686 Maintainer: Debian Python Modules Team Architecture: amd64 Source: python-scipy Version: 1.1.0-1~pn0 Depends: python3-decorator, python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3 (<< 3.6), python3 (>= 3.5~), python3:any (>= 3.3.2-2~), libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, libquadmath0 (>= 4.6), libstdc++6 (>= 5.2) Recommends: g++ | c++-compiler, python3-pil Suggests: python-scipy-doc Filename: pool/main/p/python-scipy/python3-scipy_1.1.0-1~pn0_amd64.deb Size: 10039542 MD5sum: 7d5bf8150d332242626862afca3bb0ac SHA1: 815d526582f07fd9a28820c05382ca6b68196eff SHA256: ff908b85a7ddfe10d7e932d5f8df73766180c5751486ad711661275ee182eb50 SHA512: 1482157b93730207472b36012e072f86a0a03085a66ff648c185e8bdb2f5220fa86aee18a7fabc932fe161cfa822568e718158aecdf80d6a28514e6704f04db8 Description: scientific tools for Python 3 SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package. . SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. . This package provides the Python 3 version. Homepage: http://www.scipy.org/ Package: python3-scipy-dbg Priority: optional Section: debug Installed-Size: 142162 Maintainer: Debian Python Modules Team Architecture: amd64 Source: python-scipy Version: 1.1.0-1~pn0 Depends: python3-dbg (<< 3.6), python3-numpy-dbg (>= 1:1.7.2), python3-scipy (= 1.1.0-1~pn0), python3-numpy (>= 1:1.10.0~b1), python3-numpy-abi9, python3-dbg (>= 3.5~), libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc1 (>= 1:4.0), libgfortran3 (>= 4.6), liblapack3 | liblapack.so.3, libquadmath0 (>= 4.6), libstdc++6 (>= 5.2) Filename: pool/main/p/python-scipy/python3-scipy-dbg_1.1.0-1~pn0_amd64.deb Size: 42881412 MD5sum: b1cdac86ddd4baf66d36b5e5d1cbf30c SHA1: 1838f9cf7aa00cc2d653abf9bf510d2d57a8c5f7 SHA256: 066b1e7addc15812d40e1bc2ceab8b8a8e30de72fec10b64f3693bb77a920b3b SHA512: fa1e123978b989a26dab78eafe49911583972205ded867563073d35355fe510131aed21f55e142259bbd762b777366eb81e5ce9363d73bbcc836cba1d70763f2 Description: scientific tools for Python 3 - debugging symbols SciPy supplements the popular NumPy module (python-numpy package), gathering a variety of high level science and engineering modules together as a single package. . SciPy is a set of Open Source scientific and numeric tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, genetic algorithms, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. . This package provides debugging symbols for python3-scipy. Build-Ids: 013aab29313918d5bf858fe50efca6f6179c1607 04eda18b8535eedec5edde8af2c620b1ccb9b9fb 066e74dc31a958dad23b9a3cf20650a6522ec72d 072cf61abb150926ae6e8821d3e4be2cadeddb44 08594a6d389b7450504ec38c84708e9c96fd3113 091c19c91a93b6a86475d1226fff18b05f64059e 0ac6b2af27964be76fe9302f9cbc45596cfb58f4 0d9ff826e5bfcd26b456c298c27c314e337bbc45 12b88be838d881e06b4743ac22644c1be54b7ef6 13a6019641450ff746b3e811246cba7f3baa406d 19958250db79f298544f24bcc215fa370bd41994 1a1552c8d6fad8e5515f8a5a9cef4435d0d17f87 1f56d13711e0a2b51e4af5ce51f34ea471318213 285b92d9212dafc29f1238e52e90892f691956d5 35f23878cbfa049c22f5c1041dddd48fa19ebd6f 3b18be456550d604fef1e1cd06be0f6334eab3df 3f5e24adc48125cb44f3293fa761649d62788e51 3fb09e049a87d828b15a827942899e8cde3eb1b3 4133d15729b380368ad037f6e59bbf3ae29dfdb1 43042bbaf6588b7100e9f78eef624dd6bfbdef0b 472e854bc013364e0e3c530b86fb88c358b8c2aa 47ba0661fe8a2f8663cba5486f46296e8a088f74 4a2d095cf5e4d352fbb380fd6ebbc1154989d73c 4a7356456c26614b62a93327ef04e55096e44179 4fa59e0edb45cb0ec83e229e35eff4d361645f87 521f61ab2123789beb053aecf19144a36a39cdac 524dab11ed727f03ec3ed593abdb5c5a36eca2e5 527e3f59189f3c06de1151caee46f2fd4ee9bcef 53f17842b17641aa08e8242f514900308293a5f4 54d1d007e0677c54df473fc57166b31074b32246 571f2740aadd66df0095a9e0133e6579eb6e3f27 57912448fd9c7d4587c626819381c6b55fd45dda 589d101198b8e2bd0633fdf625a71d0e457ba062 59f2ca3b7a45476b133a28fa4ef838c8313fba19 5c2d787461607734a1244592a107ea60f9029d0c 5f51a19bd2bc236f88fd8afb3d043a7f348c97af 6259191ca67b1525162cbde580e9bcf8b18e60ac 683c013f182ffb7f3f1a326599f1bcfdb6d447c4 69e128f81ebc84a30bc520ae531a9fe49aae0451 6a41eeba0690198f849078919d166a90d75ffcdb 6a5314eaf9d1a6e236a1a13d0b9dead287c6fd19 6e6048eacae3d7ef89cd77ad38c5c294d0731bc1 6ebf449f0524baa4834e589d2d93a2cc4d2bf1cf 6ffa29756c9327dfecee12098aab5eaa71259327 715f9bf77bd7430d4fbf307cda8567fd553f3d44 721fabda3cb44b285151e0c4f2be00b573c7eff6 752632971b74f6b59e67a69ec6dbe62a53868939 76baf54aae94da025627dc441a838c7cc9b937bf 7dbaf9e56adfb990805d1d487c88f3b236a97e5e 822f2d0794ba717f91992c9f802ed8d2ad4767b4 8454d500f97ec9d9b94757873f352f2537388e76 99e159e529a6b81f569c971a20d1f811cf53646b 9ffdecdc1af6f48df234fa22126bd3a5e92ce738 a27990e1d7f5257f65e0e4f03da52f9a971cba57 a506587f1ed522787dfdc19efeb900a3bdc4acb8 a65cb2bce6b26924802d46a95c10bb8a1ef05612 a707ab9ab89bb7f0467b3ef6c2941d7ab985fdd2 ab2d7f9873244214970579a225af091263ab9f85 b23b8660ad497abeb9b4b819b33df374944c0d80 b5cd123890965d0a4df3f0ad48ffa701fca08dbf b6a7c995d8493be0072592ed4667a4392611ec0a bf1c2a1d19f1a625dc5b4434c96f100c96b2992c c27f4feea704aeac6974c393626f84517cc26245 c8c6ea0021c613e5d8bab6b29eaac14248c782c6 cd360c5dbd09a275a3378074c550803a75b3691c ce77a22da580fbe4cd0985f414d8963c3bedd056 cfda2859dedfd2bfd3b41406ff218fd7cda32f23 d69b65e87448061b6612e6688832b9eeb8eba733 d8fb85cab82cf1ab44ad4abb26bafd6550f1c1f8 db6e0c97d36fbb3a0fe17c697af36d2a39dd90b5 db7aadfffd48c516a9c548a5cd87f8ff329224ee de2cfe9610114325e3c391be3b197615e040c5e9 e21c0d9b5368bf9d94907c6d7ba5ec0f756115f1 e2d06bb5ce7c3cdbcef246f9e203a402ecf5ad83 e2fd1e7c2eef88ae3c9858db34233cf52b6bd0a6 e3a5b33b9d60947ba27643d74e0011eff37d3eef e9e45085be0d630d24a6b1defcc16e65b5a535ad ea811feb7046bdc7c47a7f57e10b948e6e53431c f210b32c57df4e20dd0b5a5892609b68b15b06cb f211735966b48161ade71bc45a2da4b11e2207a7 f6bb6b4ed78458c8ba23c86a137fdb815dc69653 fb7c4d3a6dad3a9e9a30999c1601f6259d66c418 Homepage: http://www.scipy.org/ Package: python3-theano Priority: optional Section: python Installed-Size: 12261 Maintainer: Debian Science Maintainers Architecture: amd64 Source: theano Version: 0.9.0-0~pn1 Depends: python3-numpy, python3-scipy, python3-six (>= 1.9.0), python3:any (>= 3.3.2-2~), python3-dev, libblas-dev | libblas.so Recommends: python3-pydot, python3-nose, python3-nose-parameterized, theano-doc Suggests: nvidia-cuda-toolkit, python3-pycuda Filename: pool/main/t/theano/python3-theano_0.9.0-0~pn1_amd64.deb Size: 2094688 MD5sum: 680ae216e0e5be0ff96a04b66b91ac56 SHA1: 5545c5e6dc9d4a06c754f52be9b359d74c903f92 SHA256: 4bd77198fad478938469f87ececcf38b6928e8d178ba8b63ba024a898f8b6a23 SHA512: f75475410e17d09644408a4ce89a5ca62de38aeb0b5a27a67fb0c851bac182374c12ca9fbcbc67ff1ed3e9a33e337aa6226ec28841597830ed94953d5ea089f7 Description: CPU/GPU math expression compiler for Python 3 Theano is a Python library that allows one to define and evaluate mathematical expressions involving multi-dimensional arrays efficiently. It provides a high-level Numpy like expression language for functional description of calculation, rearranges expressions for speed and stability, and generates native machine instructions for fast calculation. Optionally, highly accelerated computations could be carried out on graphics cards processors. . This package contains Theano for Python 3. Homepage: http://www.deeplearning.net/software/theano/ Package: python3-xgboost Priority: optional Section: python Installed-Size: 3954 Maintainer: Benjamin Moody Architecture: amd64 Source: xgboost Version: 0.6+git20160810-0~pn1 Depends: python, python3 (>= 3~), python3-numpy, python3-scipy, python3:any (>= 3.3.2-2~), libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), libgomp1 (>= 4.9), libstdc++6 (>= 4.9) Filename: pool/main/x/xgboost/python3-xgboost_0.6+git20160810-0~pn1_amd64.deb Size: 925840 MD5sum: 73c9fe14e153a78b52836777a72cb093 SHA1: 41f0a3a31e3d74812a40598e19bfc67ae926cea1 SHA256: bc37ce3d7518fc96202f30d8aaf05e6037ffa32195b93676e77380528e21e0b5 SHA512: 0b01af81d70093d77051f99856d1debf8bd7e13e10deede7befaf6aa6a3abec484eb8e4b0068bf569cf06fb408ffd2bd0af35684baaeeb2e24871e363dd84695 Description: scalable, distributed gradient boosting library (Python 3) XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples. . This package provides the xgboost library for Python 3. Package: ruby-google-protobuf Priority: optional Section: ruby Installed-Size: 489 Maintainer: Laszlo Boszormenyi (GCS) Architecture: amd64 Source: protobuf Version: 3.6.1-1~pn0 Replaces: ruby-google-protobuf (<< 3.6.0~) Depends: ruby | ruby-interpreter, libc6 (>= 2.11), libgmp10, libruby2.3 (>= 2.3.0~preview2) Conflicts: ruby-google-protobuf (<< 3.6.0~) Filename: pool/main/p/protobuf/ruby-google-protobuf_3.6.1-1~pn0_amd64.deb Size: 161302 MD5sum: 86c95edf6b151dc21fbfbe47694f4a79 SHA1: e14eafd06cc34efa9efb132b979793ba6989a4f8 SHA256: 5447c4a446674b14604902657e105fed4d0d2189767207dda5006ed0d4093aff SHA512: 9c2f0d3dced5609b9d25a1dca29cffa7d90a21338a6984177289f9e3e22bd2d4766d77203b14a0f267b58951a010fd114c8b98305aefc4331ecef1bccfe2c816 Description: Protocol Buffers Protocol Buffers are Google's data interchange format. . This library contains the Ruby extension that implements Protocol Buffers functionality in Ruby. . The Ruby extension makes use of generated Ruby code that defines message and enum types in a Ruby DSL. You may write definitions in this DSL directly, but we recommend using protoc's Ruby generation support with .proto files. The build process in this directory only installs the extension; you need to install protoc as well to have Ruby code generation functionality. Multi-Arch: same Homepage: https://github.com/google/protobuf/ Ruby-Versions: ruby2.3 Package: wfdb Priority: optional Section: science Installed-Size: 1452 Maintainer: Benjamin Moody Architecture: amd64 Version: 10.5.25~pre2-0~pn1 Depends: libc6 (>= 2.14), libexpat1 (>= 2.0.1), libwfdb10 (>= 10.5.11) Filename: pool/main/w/wfdb/wfdb_10.5.25~pre2-0~pn1_amd64.deb Size: 422306 MD5sum: ad83e00abae0561bc37cac37c330cbba SHA1: 78c923a82bfddbfd8e9dfceca46bc785dd193c54 SHA256: 04662f44d90463fd589edba6383c23d9a77d51c1404cfaadfe68998f54637be7 SHA512: 48559397528a3fbc7bf720de4a2ee29c5b4c831ceaa44e91200677069541d28b9305e4cd020dce60fefd55111c4067adbc0506d7f9679148af137208c8196504 Description: Waveform Database Software Package The WFDB (Waveform Database) library supports creating, reading, and annotating digitized signals in a wide variety of formats. Input can be from local files or directly from web or FTP servers. Although created for use with physiologic signals such as those in PhysioBank (http://www.physionet.org/physiobank/), the WFDB library supports a broad range of general-purpose signal processing applications. . This package contains about 60 applications for creating, reading, transforming, analyzing, annotating, and viewing digitized signals, especially physiologic signals. Applications include digital filtering, event detection, signal averaging, power spectrum estimation, and many others. . This package also contains shared data files and tools that are required by many programs that use the WFDB library. Multi-Arch: foreign Package: wfdb-app-toolbox Priority: optional Section: science Installed-Size: 8727 Maintainer: Benjamin Moody Architecture: amd64 Version: 0.9.9+src-0~pn1 Depends: libc6 (>= 2.7), libwfdb10 (>= 10.5.11), wfdb, ecgpuwave, octave (>= 3.8), octave-signal Filename: pool/main/w/wfdb-app-toolbox/wfdb-app-toolbox_0.9.9+src-0~pn1_amd64.deb Size: 3178988 MD5sum: 4d4208a5228780d943f5fdfea3464bdc SHA1: 84dc4e6304d2177961b78f2e7a5e5ff7dff1c06a SHA256: ae2e12db80168565738cf7fd4545f6c9fbe58ddaed8e125530eb33ac7e5aec6d SHA512: 63038461736b8fd07e43297883354d37b2bbc75004be600e6fbdff71655781fa85caff1a37b2110b013d63c6d7580cccbe1ff7c3d0e7af66b4a4fddec4e8f809 Description: WFDB Toolbox for MATLAB and Octave A collection of functions for reading, writing, and processing physiologic signals and time series in the formats used by PhysioBank databases (among others). The Toolbox is compatible with 64-bit MATLAB and GNU Octave on GNU/Linux, Mac OS X, and MS-Windows.