facebookresearch/DetectronArchived

Features

• Object Detection - Identifies and locates multiple objects within images using bounding boxes and neural network classification.
• Instance Segmentation Engines - Generates pixel-level masks to isolate individual object instances using architectures like Mask R-CNN.
• Object Mask Generators - Implements Mask R-CNN to create precise outlines for objects using bounding boxes and segmentation masks.
• Feature Extraction - Implements deep convolutional neural networks to extract high-level semantic representations from images.
• Computer Vision Platforms - Offers a comprehensive environment for developing and experimenting with image recognition and object detection algorithms.
• Region-based Detection - Provides a two-stage pipeline using region proposal networks followed by refined classification and mask generation.
• Anchor Box Generators - Provides utilities for generating reference bounding boxes of various scales and ratios for object detection.
• Computer Vision Evaluation Tools - Supports the evaluation and prototyping of visual recognition systems using pre-trained baseline models.
• Region Alignment - Uses bilinear interpolation to preserve spatial information and avoid misalignment in region proposals.
• Multi-Scale Feature Pyramids - Utilizes architectures that aggregate hierarchical image representations to detect objects of varying sizes.
• Object Detection Models - Provides a platform for experimenting with neural network architectures designed for object localization.
• One-Stage Detectors - Implements RetinaNet as a one-stage detector utilizing focal loss to handle foreground-background class imbalance.
• Computer Vision - Research platform for state-of-the-art object detection algorithms.
• Object Detection Frameworks - FAIR's research platform for implementing advanced object detection algorithms.
• Region Based Detectors - High-performance research platform for object detection and segmentation.

Star history