#jupyter_notebook #benchmark_framework #deep_learning #dgl #graph_deep_learning #graph_neural_networks #graph_representation_learning #pytorch
https://github.com/graphdeeplearning/benchmarking-gnns
https://github.com/graphdeeplearning/benchmarking-gnns
GitHub
GitHub - graphdeeplearning/benchmarking-gnns: Repository for benchmarking graph neural networks (JMLR 2023)
Repository for benchmarking graph neural networks (JMLR 2023) - graphdeeplearning/benchmarking-gnns
#python #action_recognition #ava #benchmark #deep_learning #i3d #non_local #openmmlab #posec3d #pytorch #slowfast #spatial_temporal_action_detection #temporal_action_localization #tsm #tsn #video_understanding #x3d
https://github.com/open-mmlab/mmaction2
https://github.com/open-mmlab/mmaction2
GitHub
GitHub - open-mmlab/mmaction2: OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark
OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark - open-mmlab/mmaction2
#python #anomaly_detection #benchmark #data_mining #data_sicence #deep_learning #ensemble_learning #machine_learning #neural_networks #outlier_detection #semi_supervised_learning #supervised_learning #unsupervised_learning
https://github.com/Minqi824/ADBench
https://github.com/Minqi824/ADBench
GitHub
GitHub - Minqi824/ADBench: Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022.
Official Implement of "ADBench: Anomaly Detection Benchmark", NeurIPS 2022. - Minqi824/ADBench
#python #animal_pose_estimation #benchmark #cpm #crowdpose #deeppose #face_keypoint #freihand #hand_pose_estimation #higher_hrnet #hourglass #hrnet #human_pose #mmpose #mpii #mspn #ochuman #pose_estimation #pytorch #rsn #udp
https://github.com/open-mmlab/mmpose
https://github.com/open-mmlab/mmpose
GitHub
GitHub - open-mmlab/mmpose: OpenMMLab Pose Estimation Toolbox and Benchmark.
OpenMMLab Pose Estimation Toolbox and Benchmark. Contribute to open-mmlab/mmpose development by creating an account on GitHub.
#other #anomaly_detection #anomaly_localization #anomaly_segmentation #benchmark #computer_vision #dataset #deep_learning #defect_detection #industrial_image
https://github.com/M-3LAB/awesome-industrial-anomaly-detection
https://github.com/M-3LAB/awesome-industrial-anomaly-detection
GitHub
GitHub - M-3LAB/awesome-industrial-anomaly-detection: Paper list and datasets for industrial image anomaly/defect detection (updating).…
Paper list and datasets for industrial image anomaly/defect detection (updating). 工业异常/瑕疵检测论文及数据集检索库(持续更新)。 - M-3LAB/awesome-industrial-anomaly-detection
#rust #benchmark #cli #command_line #rust #terminal #tool
Hyperfine is a powerful tool that helps you measure how long different commands or programs take to run. Here’s why it’s useful:
- You can compare the speed of different commands or programs easily.
- It runs multiple tests and gives you detailed statistics, including average, minimum, and maximum times.
- You can prepare the system before each test (e.g., clear disk caches) to get accurate results.
- It supports various output formats like CSV, JSON, and Markdown, making it easy to analyze and share results.
- It works on many operating systems, including Windows, macOS, and Linux.
Overall, hyperfine helps you understand which commands or programs are faster and why, making it a valuable tool for optimizing performance.
https://github.com/sharkdp/hyperfine
Hyperfine is a powerful tool that helps you measure how long different commands or programs take to run. Here’s why it’s useful:
- You can compare the speed of different commands or programs easily.
- It runs multiple tests and gives you detailed statistics, including average, minimum, and maximum times.
- You can prepare the system before each test (e.g., clear disk caches) to get accurate results.
- It supports various output formats like CSV, JSON, and Markdown, making it easy to analyze and share results.
- It works on many operating systems, including Windows, macOS, and Linux.
Overall, hyperfine helps you understand which commands or programs are faster and why, making it a valuable tool for optimizing performance.
https://github.com/sharkdp/hyperfine
GitHub
GitHub - sharkdp/hyperfine: A command-line benchmarking tool
A command-line benchmarking tool. Contribute to sharkdp/hyperfine development by creating an account on GitHub.