yolov4-deepsort
zero-shot-object-tracking
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yolov4-deepsort | zero-shot-object-tracking | |
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5 | 10 | |
1,287 | 350 | |
- | 1.4% | |
0.0 | 0.6 | |
23 days ago | 16 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU General Public License v3.0 only |
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yolov4-deepsort
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Trying to count hikers/day in a video stream
I have a video stream of a hiking trail and am trying to count the number of hikers per day. The camera never moves. At night you can also see headlamps :). Direction not as important as just a count of bodies passing through the image in a given time period. https://drive.google.com/file/d/1BwLzyHhrLafyAj5kYn-AfDVBtBBVQCsO/view. I've tried https://github.com/theAIGuysCode/yolov4-deepsort on the stream but it isn't picking up the people, maybe they're too low res for TF Object Detection?
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How do I train the DeepSORT tracker for a custom class?
I am trying to track objects in a sequence of images in order to count them. I was looking around for robust trackers since in my case, the camera moves with respect to the object. I found the DeepSORT tracker online and it seems like the solution to my problem. However, I am not sure of how I could train it for my own custom classes. I am currently looking at this repository and it seems to almost do the things I want, except for the counting part. Can anyone explain to me how I can train the DeepSORT tracker for my own classes? I am already training a YOLOv4 model on these custom classes. As a result, I have collected a labelled dataset for the training and validation purposes, and if I have to use images for the training.
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Help needed with object tracker implementation
I have tried to implement the YOLOv4 + DeepSort tracking from the AI Guys code presented here, just to get an idea of how to go about this, but from what I understand, I will need to train the DeepSORT tracker for detecting my own classes. I do not know how to do that.
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Will Object Detection models trained on images work on videos too?
You can try a detection and tracking paradigm for videos - it would be a lot more accurate than detection only without the need re-detect every frame which spends a lot of compute. E.g.: https://github.com/theAIGuysCode/yolov4-deepsort
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Installing tensorflow with gpu makes me want to blow my brains out
And totally unecessary!! Next day, I discovered a GitHub project that simply used conda, as below.
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?
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.3.1, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
multi-object-tracker - Multi-object trackers in Python
ssd_keras - A Keras port of Single Shot MultiBox Detector
remote - Moved to https://github.com/labmlai/labml/tree/master/remote
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
pyenv-installer - This tool is used to install `pyenv` and friends.
yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x