xview-yolov3
FastMOT
| xview-yolov3 | FastMOT | |
|---|---|---|
| 1 | 2 | |
| 245 | 1,095 | |
| 0.8% | - | |
| 6.3 | 0.0 | |
| 3 days ago | over 2 years ago | |
| Python | Python | |
| GNU Affero General Public License v3.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
xview-yolov3
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How hard is this task - counting the number of cars from an aerial video clip
Use pretrained object detection models on aerial datasets. One of the datasets in xview dataset or DOTA dataset. You can use this repository : https://github.com/ultralytics/xview-yolov3
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)
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
multi-object-tracker - Multi-object trackers in Python
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.
fast-reid - SOTA Re-identification Methods and Toolbox
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.
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.
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking