cvat
yolov5
cvat | yolov5 | |
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26 | 129 | |
11,287 | 47,071 | |
- | 1.8% | |
9.8 | 8.8 | |
28 days ago | 4 days ago | |
TypeScript | Python | |
MIT License | GNU Affero General Public License v3.0 |
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cvat
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision.
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Need help identifying a good open source data annotation tool
CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start.
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OKENYO - Eyes to the Sky
ref https://github.com/opencv/cvat/issues/6061
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Way to label yolov7 images fast
an open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. there is an integration for yolov5, but without modification it only loads the pretrained models.
- [D] Choosing the image labeling tool
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Segment Anything Model is now available in the open-source CVAT
This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat) and coming soon to CVAT.ai cloud (http://cvat.ai/)! Please use it for your computer vision projects to segment images faster.
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How to build computer vision dataset labeling team in-house
You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two optionsâ-âlocally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS).
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CVAT Release v2.3.0: Brush tool, WebHooks, and Social auth
In this release, CVAT introduced new features based on our vision and suggestions in the CVAT community, plus addressed more than 20+ reported bugs.
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CVAT Course. Lecture #3 - Integration
You can find more information here Waiting for your feedback here: Discord, LinkedIn, Gitter, GitHub
yolov5
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Ref https://www.youtube.com/watch?v=0GwnxFNfZhM https://github.com/ultralytics/yolov5 https://dev.to/gfstealer666/kaaraich-yolo-alkrithuemainkaartrwcchcchabwatthu-object-detection-3lef https://www.kaggle.com/datasets/devdgohil/the-oxfordiiit-pet-dataset/data
- How would i go about having YOLO v5 return me a list from left to right of all detected objects in an image?
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Building a Drowsiness Detection Web App from scratch - pt2
!git clone https://github.com/ultralytics/yolov5.git ## Navigate to the model %cd yolov5/ ## Install requirements !pip install -r requirements.txt ## Download the YOLOv5 model !wget https://github.com/ultralytics/yolov5/releases/download/v6.0/yolov5s.pt
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[Help: Project] Transfer Learning on YOLOv8
Specifically what I did was take the coco128.yaml, added 6 new classes from Dataset A (which have already been converted to YOLO Darknet TXT), from index 0-5 and subsequently adjusted the indices of the other COCO classes. The I proceeded to train and validate on Dataset A for 20 epochs.
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Changing labels of default YOLOv5 model
I am using the default YOLOv5m6 model here with sahi/yolov5 library for my object detection project. I want to change just some of labels - for example when YOLO detects a human, I want it to label the human as "threat", not "person". Is there any way I can do it just changing some code, or I should train the model from scratch by just changing labels?
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First time working with computer vision, need help figuring out a problem in my model
You should add them without annotations. Go through this.
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AI Camera?
You are correct and if you check the firmware, it's yet another famous 3rd party project without attribution, namely https://github.com/ultralytics/yolov5
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First non-default print on K1 - success
On one side, being a Linux user for 24 years now, it annoys me that they rip off code and claiming it as theirs again, thus violating licenses, but on the other thanks to k3d's exploit I'm able to tinker more with the machine and if needed do (selective) updates by hand then with a closed source system. It's not just "klipper", with klipper, fluidd and moonraker, it's also ffmpeg and mjpegstreamer. It's gonna be interesting since they also use a project that isn't just GPL, but APGL (in short "If your software gives service online, you have to publish the source code of it and any library that it borrows functions from.") - they use yolov5 (for AI).
- How does the background class work in object detection?
What are some alternatives?
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
mmdetection - OpenMMLab Detection Toolbox and Benchmark
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.
detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
coco-annotator - :pencil2: Web-based image segmentation tool for object detection, localization, and keypoints
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
django-rest-framework - Web APIs for Django. ðļ
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
labelbox-custom-labeling-apps - Explore example custom labeling apps built with Labelbox SDK
OpenCV - Open Source Computer Vision Library