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Computer Vision Tasks · Awesome GitHub Repositories

4 repos

Awesome GitHub RepositoriesComputer Vision Tasks

Specific computational operations performed on visual data, such as classification, detection, or tracking.

Explore 4 awesome GitHub repositories matching artificial intelligence & ml · Computer Vision Tasks. Refine with filters or upvote what's useful.

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  • hacksider/Deep-Live-Cam

    hacksider/Deep-Live-Cam

    79,568GitHubView on GitHub↗

    Deep-Live-Cam is a generative video transformation tool designed for real-time facial manipulation and cinematic enhancement. It functions as a local-first AI runtime, performing all media processing directly on the user's hardware to ensure complete data privacy without external network dependencies. By utilizing a hi

    Pythonaiai-deep-fakeai-face
  • ultralytics/yolov5

    ultralytics/yolov5

    56,830GitHubView on GitHub↗

    YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning

    Pythoncoremldeep-learningios
  • facebookresearch/segment-anything

    facebookresearch/segment-anything

    53,431GitHubView on GitHub↗

    This project provides a deep learning architecture designed to identify and isolate distinct objects within images by generating precise pixel-level masks. It functions as a browser-based inference engine, enabling the execution of complex machine learning models directly within web environments without requiring serve

    Jupyter Notebook
  • ultralytics/ultralytics

    ultralytics/ultralytics

    53,426GitHubView on GitHub↗

    Ultralytics is a comprehensive computer vision framework designed for training, validating, and deploying deep learning models across a wide range of visual recognition tasks. It provides a unified interface for core operations including object detection, instance segmentation, pose estimation, and image classification

    Pythonclicomputer-visiondeep-learning

Explore sub-tags

  • Classification Model TrainingProcedures for training image classification models.
  • Classification Model ValidationsProcedures for measuring the accuracy of image classification models using metrics like top-1 and top-5 error rates.
  • Image Classification ModelsPre-trained models capable of analyzing visual content to assign descriptive labels to entire images.
  • Instance SegmentationThe task of detecting and delineating each distinct object of interest in an image at the pixel level.
  • Multi-Face Tracking SystemsSystems capable of identifying and monitoring multiple distinct individuals within a single visual frame.
  • Multi-Object TrackersAlgorithms that maintain identity and trajectory for multiple objects across sequential video frames.
  • Object Pose EstimationsTechniques for identifying and tracking the spatial orientation and keypoint coordinates of objects or human subjects within visual data.
  • Open-Vocabulary SegmentersModels capable of segmenting objects based on arbitrary text or visual prompts without fixed category constraints.
  • Oriented Object DetectionDetection methods that identify objects using rotated bounding boxes defined by orientation angles rather than axis-aligned boxes.
  • Prompt-Based Mask DecodersGenerating spatial masks from sparse point or box inputs.