FastMOT
Deep-SORT-YOLOv4
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| FastMOT | Deep-SORT-YOLOv4 | |
|---|---|---|
| 2 | 1 | |
| 1,095 | 492 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | about 3 years ago | |
| Python | Python | |
| MIT License | GNU General Public License v3.0 only |
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FastMOT
- Does Multi Object Tracking work better (precision/recall) on videos than jury rigging a SOTA image object detection to work on videos?
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Assign ID and track moving object with optical flow
On failure, you can try using a re-identification methods like FastReid: https://github.com/JDAI-CV/fast-reid in combination with your detector. A good pipeline that combines everything you seem to need is here: https://github.com/GeekAlexis/FastMOT. It uses a combination of Yolov4 (detector) + Kalman filters, Optical flow (tracker) and FastReid (re-identification)
Deep-SORT-YOLOv4
What are some alternatives?
multi-object-tracker - Multi-object trackers in Python
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
fast-reid - SOTA Re-identification Methods and Toolbox
AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
TFJS-object-detection - Real-time custom object detection in the browser using tensorflow.js
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
YOLO-Coco-Dataset-Custom-Classes-Extractor - Get specific classes from the Coco Dataset with annotations for the Yolo Object Detection model for building custom object detection models.