yolo_tracking
zero-shot-object-tracking
yolo_tracking | zero-shot-object-tracking | |
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8 | 10 | |
6,126 | 351 | |
- | 0.9% | |
9.9 | 0.6 | |
7 days ago | 23 days ago | |
Python | Python | |
GNU Affero General Public License v3.0 | GNU General Public License v3.0 only |
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yolo_tracking
- FLiPN-FLaNK Stack Weekly for 17 April 2023
- Person head count
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[P] Vehicle detection with pytorch
You can use YOLOv5 with the StrongSORT. We have been using it for human detection and tracking. It works really well and YOLOv5 in general really easy to use and implement out of the box. here is the repo that we are using.
- ID Swap issue in multi-object tracking.
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tracking-by-detection, multiple object tracking algorithm
Try looking into DeepSort, which uses a deep association metric in addition to the traditional SORT algorithm to kind of improve upon the ID reassignment issue. However, I suspect you would have to come up with your own re-id model since you have a unique object you're trying to detect. Here's the paper . I've had decent results using https://github.com/mikel-brostrom/Yolov5_DeepSort_OSNet as an out of the box implementation for coco object. It's written in PyTorch.
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Object tracking in videos?
https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch I see this combination mentioned a decent amount
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Deepsort stuck in tentative
https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch/blob/master/deep_sort_pytorch/deep_sort/sort/tracker.py.
zero-shot-object-tracking
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How to Track Flying Objects?
I’ve seen a bunch of drone-detection computer vision projects. Usually they’re detecting dromes from other drones though (Eg for autonomous racing[1] or drone-defense).
A challenge with doing it from the ground is that the drones will be quite small relative to the size of the image. With sufficient compute and several cameras a tiling-based approach[2] should work!
If you want to do unique-identification you’ll also need object tracking[3].
This is exactly the type of project Roboflow (our startup) is built to empower! Happy to chat/help further (Eg we might be able to help source a good dataset to start from). And if it’s for non-commercial use it should be completely free.
[1] https://blog.roboflow.com/drone-computer-vision-autopilot/
[2] https://blog.roboflow.com/detect-small-objects/
[3] https://blog.roboflow.com/zero-shot-object-tracking/
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Object tracking in videos?
We use CLIP for object tracking with pretty good results (with no second model train required). https://blog.roboflow.com/zero-shot-object-tracking/
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Hacker News top posts: Aug 28, 2021
Zero Shot Object Tracking\ (4 comments)
- Need help in camera selection
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Zero Shot Object Tracking
It uses an object detection model (in our example code[1], we used one from Roboflow Universe[2] but you should be able to use any object detection model) and then sends a crop of each detected box to CLIP to get the feature vector that Deep SORT uses to differentiate between and track instances across frames.
[1] https://github.com/roboflow-ai/zero-shot-object-tracking
[2] https://universe.roboflow.com
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[P] Zero-Shot Object Tracking with CLIP and Deep SORT
Repo: https://github.com/roboflow-ai/zero-shot-object-tracking
- Zero-Shot Object Tracking with CLIP and Deep SORT
- Show HN: Zero-Shot Object Tracking
What are some alternatives?
yolact - A simple, fully convolutional model for real-time instance segmentation.
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
ssd_keras - A Keras port of Single Shot MultiBox Detector
classy-sort-yolov5 - Ready-to-use realtime multi-object tracker that works for any object category. YOLOv5 + SORT implementation.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.