yolo-tf2
zero-shot-object-tracking
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yolo-tf2 | zero-shot-object-tracking | |
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1 | 10 | |
747 | 350 | |
- | 1.4% | |
7.6 | 0.6 | |
almost 2 years ago | 14 days ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 only |
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yolo-tf2
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How to write a resume for python / ML jobs?
my most useful project is yolo object detector implementation in tf2 and I'm currently working on 2 other projects, one of which is the implementation of various drl algorithms in tf and the other project will be based on the latter and it's concerned with trading. The rest are more of scripts rather than projects ex: web scraping, file management, programming challenges ...
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.
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
norfair - Lightweight Python library for adding real-time multi-object tracking to any detector.
Beginner-Traffic-Light-Detection-OpenCV-YOLOv3 - This is a python program using YOLO and OpenCV to detect traffic lights. Works in The Netherlands, possibly other countries
FastMOT - High-performance multiple object tracking based on YOLO, Deep SORT, and KLT 🚀
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
ssd_keras - A Keras port of Single Shot MultiBox Detector
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
yolov4-deepsort - Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.