classy-sort-yolov5
yolo_tracking
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classy-sort-yolov5 | yolo_tracking | |
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1 | 8 | |
107 | 6,110 | |
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0.0 | 9.9 | |
over 1 year ago | 4 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU Affero General Public License v3.0 |
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classy-sort-yolov5
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.
What are some alternatives?
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
yolact - A simple, fully convolutional model for real-time instance segmentation.
zero-shot-object-tracking - Object tracking implemented with the Roboflow Inference API, DeepSort, and OpenAI CLIP.
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
multi-object-tracker - Multi-object trackers in Python
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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.
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
ByteTrack-ONNX-Sample - ByteTrack(Multi-Object Tracking by Associating Every Detection Box)のPythonでのONNX推論サンプル
crop - Character Recognition Of Plates using yolov5