Yolo_mark
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| Yolo_mark | sort | |
|---|---|---|
| 6 | 8 | |
| 1,783 | 3,719 | |
| - | - | |
| 10.0 | 3.3 | |
| over 3 years ago | 5 months ago | |
| C++ | Python | |
| The Unlicense | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Yolo_mark
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Way to label yolov7 images fast
I've used Yolo_mark (https://github.com/AlexeyAB/Yolo_mark) with success when needing to label a few hundred thousand images. Its still a manual solution, but there are keyboard shortcuts for navigating between images and classes, and with some practice you can get through a ton of images quite quickly.
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Implementation of YOLO in python or C++?
What are you talking about? Darknet -- where YOLO started! -- is written in C and C++. Check the active repo: https://github.com/AlexeyAB/darknet
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I was excited about YOLOv7, so I built a sharable object detection application with VDP and Streamlit.
When YOLOv7 was out, I built a web app to test it against the classic YOLOv4 and shared it with my team, then deployed it online to share with the community.
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HOW to find MOTA and MOTP for MOT evaluation metrics?
Because I need to calculate MOTA and MOTP for the tracking metrics. please anyone with this concept help me as I am beginner to the computer vision. Incase if it helps I am working based on the github https://github.com/AlexeyAB/darknet
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How to improve a YoloV5 model after the first training?
My work heavily involves the use of the yolo algorithm such as optimising it for performance on mobile devices. Yolov5 is made by a private company that has been pushing sub bar models for a while. I've benchmarked their smallest models comparing them to Yolov4 tiny and the results were staggering, v4 being around 3-4 times faster. Yolov4 has way more resources for development, I highly suggest checking out this repo https://github.com/AlexeyAB/darknet
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[D] What are people using to organize large groups of people for data labelling?
YOLO Mark
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- [D] how does military auto turrets like CWIS not get confused when there are multiple targets?
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Similari 0.26.2: MOT framework with Python bindings
Similari is a Rust/Python framework aimed at building sophisticated tracking systems. With Similari, you can develop highly efficient parallelized SORT, DeepSORT, and other sophisticated multiple-object tracking engines.
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How to improve a YoloV5 model after the first training?
One interesting thing to consider is about using a new model's output as training data is the following. If you use some object tracking algorithm like SORT, you might be able to find frames where the object was "tracked" even though the model didn't detect the object (some type of flickering). In this case, you're able to run the model on video and make it better by giving it these new bounding boxes based on "tracking". Does that make sense?
- Temporal filtering of CNN detectors
- How to track an object between detections with a kalman filter?
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[P] Gait Recognition in the wild
The model is an ST-GCN trained in a completely unsupervised manner, from a LOT of skeleton sequences. Pose estimation was performed with AlphaPose, and tracked using SORT.
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Is it possible to track objects on the go?
Yes it is possible! It's an addition to object detection, so I suggest you look for "object detection tracking". You can find articles like this one which refers to Python libraries like this one.
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I made a traffic light detection program with a self-trained dataset
congratz! that's a great project. since you have the detector operating on videos, you could add a simple tracking-by-detection method like SORT. https://github.com/abewley/sort#using-sort-in-your-own-project it's really easy to use, and creates temporally constistent tracks by associating detections in successive frames.
What are some alternatives?
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
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
py-motmetrics - :bar_chart: Benchmark multiple object trackers (MOT) in Python
deep_sort - Simple Online Realtime Tracking with a Deep Association Metric
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System
TensorRT-For-YOLO-Series - tensorrt for yolo series (YOLOv8, YOLOv7, YOLOv6, YOLOv5), nms plugin support
Similari - A framework for building high-performance real-time multiple object trackers
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
deprecated-core - 🔮 Instill Core contains components for supporting Instill VDP and Instill Model
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK