Yolo_mark | marking bounded boxes of objects in images for training | Computer Vision library

by AlexeyAB C++ Version: Current License: Unlicense

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | Yolo_mark Summary

Yolo_mark is a C++ library typically used in Artificial Intelligence, Computer Vision applications. Yolo_mark has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Windows & Linux GUI for marking bounded boxes of objects in images for training Yolo v3 and v2. Supported both: OpenCV 2.x and OpenCV 3.x. 3.1 Download pre-trained weights for the convolutional layers (76 MB): 3.2 Put files: yolo-obj.cfg, data/train.txt, data/obj.names, data/obj.data, darknet19_448.conv.23 and directory data/img near with executable darknet-file, and start training: darknet detector train data/obj.data yolo-obj.cfg darknet19_448.conv.23. For a detailed description, see:

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Yolo_mark has a medium active ecosystem.

It has 1751 star(s) with 671 fork(s). There are 70 watchers for this library.

It had no major release in the last 6 months.

There are 135 open issues and 59 have been closed. On average issues are closed in 70 days. There are 13 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Yolo_mark is current.

Quality

Yolo_mark has 0 bugs and 0 code smells.

Security

Yolo_mark has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Yolo_mark code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Yolo_mark is licensed under the Unlicense License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Yolo_mark releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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Yolo_mark Key Features

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Yolo_mark Examples and Code Snippets

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Community Discussions

Trending Discussions on Yolo_mark

Create pre-trained weights for detection without darknet / torch

Why do I get this error? 'NoneType' object has no attribute 'shape' in opencv

QUESTION

Create pre-trained weights for detection without darknet / torch

Asked 2020-Nov-23 at 13:57

I want to train my data and create a weights file to train my YOLOV3 network. The objects in my database are not in COCO's classes so I do not want to use their weights file. I also have a limitation - I can not use darknet and I also prefer not to use the torch library.

The files I have: (according https://github.com/AlexeyAB/Yolo_mark/issues/60#issuecomment-401854885)

yolov3-custom.cfg according my classes
obj.names with my class's names
train.txt + test.txt with list of image's location
folder with images+ labels yolo format (object-class, x, y, width, height)
obj.data

What can I do?

...

ANSWER

Answered 2020-Nov-20 at 14:43

You can still use the pre-trained weights on ImageNet if you want to start with pre-trained weights. If you have different classes than the COCO dataset that's no problem. You can define your own classes, and start training with the pre-trained weights. During training, the weights will be updated to detect your custom classes.

You can use these weights for YOLOv3: "https://pjreddie.com/media/files/yolov3.weights"

Source https://stackoverflow.com/questions/64876507

QUESTION

Why do I get this error? 'NoneType' object has no attribute 'shape' in opencv

Asked 2020-Sep-24 at 19:03

I'm working on real-time clothing detection. so i borrowed the code from GitHub like this:https://github.com/rajkbharali/Real-time-clothes-detection but (H, W) = frame.shape[:2]:following error in last line. Where should I fix it?

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ANSWER

Answered 2020-Sep-24 at 19:03

The reason behind your error is that the frame is None(Null). Sometimes, the first frame that is captured from the webcam is None mainly because (1) the webcam is not ready yet ( and it takes some extra second for it to get ready) or (2) the operating system does not allow your code to access the webcam.

In the first case, before you do anything on the frame you need to check whether the frame is valid or not :

Source https://stackoverflow.com/questions/64045677

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Yolo_mark

You can download it from GitHub.

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For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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