#python #automl #computer_vision #data_science #deep_learning #distributed_computing #ensemble_learning #gluon #image_classification #machine_learning #mxnet #natural_language_processing #object_detection #pytorch #structured_data #transfer_learning
https://github.com/awslabs/autogluon
https://github.com/awslabs/autogluon
GitHub
GitHub - autogluon/autogluon: Fast and Accurate ML in 3 Lines of Code
Fast and Accurate ML in 3 Lines of Code. Contribute to autogluon/autogluon development by creating an account on GitHub.
#jupyter_notebook #artificial_intelligence #azure #computer_vision #convolutional_neural_networks #data_science #deep_learning #image_classification #image_processing #jupyter_notebook #kubernetes #machine_learning #microsoft #object_detection #operationalization #python #similarity #tutorial
https://github.com/microsoft/computervision-recipes
https://github.com/microsoft/computervision-recipes
GitHub
GitHub - microsoft/computervision-recipes: Best Practices, code samples, and documentation for Computer Vision.
Best Practices, code samples, and documentation for Computer Vision. - microsoft/computervision-recipes
#other #awesome #awesome_list #classification #dataset #deep_learning #forecasting #image_classification #machine_learning #multi_label_classification #series_forecasting
https://github.com/NirantK/awesome-project-ideas
https://github.com/NirantK/awesome-project-ideas
GitHub
GitHub - NirantK/awesome-project-ideas: Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas - NirantK/awesome-project-ideas
#python #artificial_intelligence #attention_mechanism #computer_vision #image_classification #transformers
https://github.com/lucidrains/vit-pytorch
https://github.com/lucidrains/vit-pytorch
GitHub
GitHub - lucidrains/vit-pytorch: Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with…
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch - lucidrains/vit-pytorch
#python #ade20k #image_classification #imagenet #mask_rcnn #mscoco #object_detection #semantic_segmentation #swin_transformer
https://github.com/microsoft/Swin-Transformer
https://github.com/microsoft/Swin-Transformer
GitHub
GitHub - microsoft/Swin-Transformer: This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer…
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows". - microsoft/Swin-Transformer
#python #text_classification #text #transformer #vision #image_classification #feedforward_neural_network #language_model #fourier_transform #fnet
https://github.com/rishikksh20/FNet-pytorch
https://github.com/rishikksh20/FNet-pytorch
GitHub
GitHub - rishikksh20/FNet-pytorch: Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms - GitHub - rishikksh20/FNet-pytorch: Unofficial implementation of Google's FNet: Mixing Tokens with...
#python #nlp #sparsity #tensorflow #keras #pytorch #deep_learning_algorithms #image_classification #deep_learning_library #pruning #object_detection #automl #computer_vision_algorithms #onnx #deep_learning_models #sparsification #pruning_algorithms #smaller_models #model_sparsification #sparsification_recipes #recipe_driven_approaches
https://github.com/neuralmagic/sparseml
https://github.com/neuralmagic/sparseml
GitHub
GitHub - neuralmagic/sparseml: Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling…
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models - neuralmagic/sparseml
#python #image_classification #image_recognition #pretrained_models #knowledge_distillation #product_recognition #autoaugment #cutmix #randaugment #gridmask #deit #repvgg #swin_transformer #image_retrieval_system
https://github.com/PaddlePaddle/PaddleClas
https://github.com/PaddlePaddle/PaddleClas
GitHub
GitHub - PaddlePaddle/PaddleClas: A treasure chest for visual classification and recognition powered by PaddlePaddle
A treasure chest for visual classification and recognition powered by PaddlePaddle - PaddlePaddle/PaddleClas
#typescript #annotation #annotation_tool #annotations #boundingbox #computer_vision #computer_vision_annotation #dataset #deep_learning #image_annotation #image_classification #image_labeling #image_labelling_tool #imagenet #labeling #labeling_tool #semantic_segmentation #tensorflow #video_annotation
https://github.com/openvinotoolkit/cvat
https://github.com/openvinotoolkit/cvat
GitHub
GitHub - cvat-ai/cvat: Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams…
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. - cvat-ai/cvat
#other #classification #convolutional_neural_networks #dataset #datasets #deep_learning #deep_neural_networks #image_classification #keras #machine_learning #python #pytorch #remote_sensing #satellite_data #satellite_imagery #satellite_images #sentinel #tensorflow
https://github.com/robmarkcole/satellite-image-deep-learning
https://github.com/robmarkcole/satellite-image-deep-learning
GitHub
GitHub - satellite-image-deep-learning/techniques: Techniques for deep learning with satellite & aerial imagery
Techniques for deep learning with satellite & aerial imagery - satellite-image-deep-learning/techniques
#python #action_recognition #anomaly_detection #audio_processing #background_removal #crowd_counting #deep_learning #face_detection #face_recognition #fashion_ai #gan #hand_detection #image_classification #image_segmentation #machine_learning #neural_network #object_detection #object_recognition #object_tracking #pose_estimation
https://github.com/axinc-ai/ailia-models
https://github.com/axinc-ai/ailia-models
GitHub
GitHub - axinc-ai/ailia-models: The collection of pre-trained, state-of-the-art AI models for ailia SDK
The collection of pre-trained, state-of-the-art AI models for ailia SDK - axinc-ai/ailia-models
#python #bumble #efficientnet #image_classification #tensorflow
https://github.com/bumble-tech/private-detector
https://github.com/bumble-tech/private-detector
GitHub
GitHub - bumble-tech/private-detector: Bumble's Private Detector - a pretrained model for detecting lewd images
Bumble's Private Detector - a pretrained model for detecting lewd images - GitHub - bumble-tech/private-detector: Bumble's Private Detector - a pretrained model for detecting lewd images
#jupyter_notebook #computer_vision #deep_learning #deep_neural_networks #image_classification #image_segmentation #object_detection #pytorch #tutorial #yolov5 #yolov6 #yolov7
https://github.com/roboflow-ai/notebooks
https://github.com/roboflow-ai/notebooks
GitHub
GitHub - roboflow/notebooks: A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything…
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM ...
#python #deep_learning #image_classification #imagenet #mobilenet #pytorch #regnet #resnet #resnext #senet #shufflenet #swin_transformer
https://github.com/open-mmlab/mmclassification
https://github.com/open-mmlab/mmclassification
GitHub
GitHub - open-mmlab/mmpretrain: OpenMMLab Pre-training Toolbox and Benchmark
OpenMMLab Pre-training Toolbox and Benchmark. Contribute to open-mmlab/mmpretrain development by creating an account on GitHub.
#jupyter_notebook #computer_vision #deep_learning #image_classification #imagenet #neural_network #object_detection #pretrained_models #pretrained_weights #pytorch #semantic_segmentation #transfer_learning
https://github.com/Deci-AI/super-gradients
https://github.com/Deci-AI/super-gradients
GitHub
GitHub - Deci-AI/super-gradients: Easily train or fine-tune SOTA computer vision models with one open source training library.…
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS. - Deci-AI/super-gradients
#cplusplus #ai #behaviour_analysis #cv #deep_learning #deepstream #face_recognition #feature_extraction #gstreamer #image_classification #image_enhancement #image_segmentation #license_plate_recognition #object_detection #opencv #reid #similarity_search #video_analysis #video_processing
https://github.com/sherlockchou86/VideoPipe
https://github.com/sherlockchou86/VideoPipe
GitHub
GitHub - sherlockchou86/VideoPipe: A cross-platform video structuring (video analysis) framework. If you find it helpful, please…
A cross-platform video structuring (video analysis) framework. If you find it helpful, please give it a star: ) 跨平台的视频结构化(视频分析)框架,觉得有帮助的请给个星星 : ) - GitHub - sherlockchou86/VideoPipe: A cross-plat...
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#python #deep_learning #hub #image_classification #instance_segmentation #machine_learning #obb #object_detection #pose #pytorch #tracking #ultralytics #yolo #yolo_world #yolo_world_v2 #yolo11 #yolov10 #yolov8 #yolov9
Ultralytics YOLO11 is a state-of-the-art model for object detection, segmentation, classification, and pose estimation. It is fast, accurate, and easy to use, making it suitable for various tasks. You can install it using pip (`pip install ultralytics`) and use it via the command line or Python scripts. The model comes with extensive documentation and community support through Discord, Reddit, and forums. Additionally, Ultralytics offers integrations with other AI platforms like Roboflow and ClearML to enhance your workflow. This tool benefits users by providing high-performance AI capabilities with minimal setup and robust community resources for assistance.
https://github.com/ultralytics/ultralytics
Ultralytics YOLO11 is a state-of-the-art model for object detection, segmentation, classification, and pose estimation. It is fast, accurate, and easy to use, making it suitable for various tasks. You can install it using pip (`pip install ultralytics`) and use it via the command line or Python scripts. The model comes with extensive documentation and community support through Discord, Reddit, and forums. Additionally, Ultralytics offers integrations with other AI platforms like Roboflow and ClearML to enhance your workflow. This tool benefits users by providing high-performance AI capabilities with minimal setup and robust community resources for assistance.
https://github.com/ultralytics/ultralytics
GitHub
GitHub - ultralytics/ultralytics: Ultralytics YOLO 🚀
Ultralytics YOLO 🚀. Contribute to ultralytics/ultralytics development by creating an account on GitHub.
#javascript #annotation #annotation_tool #annotations #boundingbox #computer_vision #data_labeling #dataset #datasets #deep_learning #image_annotation #image_classification #image_labeling #image_labelling_tool #label_studio #labeling #labeling_tool #mlops #semantic_segmentation #text_annotation #yolo
Label Studio is a free, open-source tool that helps you label different types of data like images, audio, text, videos, and more. It has a simple and user-friendly interface that makes it easy to prepare or improve your data for machine learning models. You can customize it to fit your needs and export labeled data in various formats. It supports multi-user labeling, multiple projects, and integration with machine learning models for pre-labeling and active learning. You can install it locally using Docker, pip, or other methods, or deploy it in cloud services like Heroku or Google Cloud Platform. This tool streamlines your data labeling process and helps you create more accurate ML models.
https://github.com/HumanSignal/label-studio
Label Studio is a free, open-source tool that helps you label different types of data like images, audio, text, videos, and more. It has a simple and user-friendly interface that makes it easy to prepare or improve your data for machine learning models. You can customize it to fit your needs and export labeled data in various formats. It supports multi-user labeling, multiple projects, and integration with machine learning models for pre-labeling and active learning. You can install it locally using Docker, pip, or other methods, or deploy it in cloud services like Heroku or Google Cloud Platform. This tool streamlines your data labeling process and helps you create more accurate ML models.
https://github.com/HumanSignal/label-studio
GitHub
GitHub - HumanSignal/label-studio: Label Studio is a multi-type data labeling and annotation tool with standardized output format
Label Studio is a multi-type data labeling and annotation tool with standardized output format - HumanSignal/label-studio