multi_object_tracking
norfair
| multi_object_tracking | norfair | |
|---|---|---|
| 1 | 4 | |
| 1 | 2,297 | |
| - | 1.1% | |
| 2.7 | 7.0 | |
| about 3 years ago | 25 days ago | |
| Python | Python | |
| GNU Affero General Public License v3.0 | BSD 3-clause "New" or "Revised" License |
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multi_object_tracking
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Show HN: Critter.Camera – Browser based motion detection and image capture
I also tackled the problem of moving-window brightness calibration in a related (but more constrained) problem --- tracking water fleas moving in a tank of water where an overhead light might periodically turn on and wash out the picture.
I essentially subtracted the current frame from the max across a moving window.
I'd be interested to chat about it if you like, my email is in my profile. The code is at https://github.com/nuchi/multi_object_tracking
norfair
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Seeking Efficient Video Object Tracking and or Video Segmentation Software for Research
If you're familiar with Python you can try using Norfair. It's a lightweight Python library for adding real-time multi-object tracking to any detector. There are lots of examples for you to try, they mostly differ on the object detector.
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Help combining custom detector (yolo) with a tracker.
Yyou can use norfair: https://github.com/tryolabs/norfair
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Empresa uruguaya que SI recomendarías
Tryolabs
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Tracker on top of YOLO algorithm?
Depending on your task normal SORT would work as well (No retraining required, just some Kallman filter and some other techniques). The library https://github.com/tryolabs/norfair has implemented SORT and can be extended with DeepSORT if you want.
What are some alternatives?
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
multi-object-tracker - Multi-object trackers in Python
FairMOT - [IJCV-2021] FairMOT: On the Fairness of Detection and Re-Identification in Multi-Object Tracking
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
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.
kalmanpy - Implementation of Kalman Filter in Python
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
Kornia - Geometric Computer Vision Library for Spatial AI
UNINEXT - [CVPR'23] Universal Instance Perception as Object Discovery and Retrieval
PeekingDuck - A modular framework built to simplify Computer Vision inference workloads.