yolov4-tiny-pytorch | This is a YoloV4-tiny-pytorch source code that can be

 by   bubbliiiing Python Version: v3.1 License: MIT

kandi X-RAY | yolov4-tiny-pytorch Summary

kandi X-RAY | yolov4-tiny-pytorch Summary

yolov4-tiny-pytorch is a Python library. yolov4-tiny-pytorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This is a YoloV4-tiny-pytorch source code that can be used to train your own model.
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            kandi-support Support

              yolov4-tiny-pytorch has a low active ecosystem.
              It has 656 star(s) with 171 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 71 open issues and 27 have been closed. On average issues are closed in 28 days. There are 5 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of yolov4-tiny-pytorch is v3.1

            kandi-Quality Quality

              yolov4-tiny-pytorch has 0 bugs and 0 code smells.

            kandi-Security Security

              yolov4-tiny-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              yolov4-tiny-pytorch code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              yolov4-tiny-pytorch is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              yolov4-tiny-pytorch releases are available to install and integrate.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed yolov4-tiny-pytorch and discovered the below as its top functions. This is intended to give you an instant insight into yolov4-tiny-pytorch implemented functionality, and help decide if they suit your requirements.
            • Train one epoch
            • Called when training is finished
            • Convert an image
            • Get the ground - truth map
            • Convert image to text
            • Downloads the ground - truth test results
            • Generate the ground - truth map
            • Draw a plot function
            • Adjust axes limits
            • Draw text inside an image
            • Forward computation
            • Compute the clip of the curve
            • BELoss
            • Reads the class names
            • Read anchors from file
            • Show configuration options
            • Converts an annotation file into an annotation file
            • Load image data
            • Write the ground truth test results
            • Return a function for learning rates
            • Convert to onnx
            • Calculate FPS
            • Detect heatmap image
            • Detect image
            • Kmeans clustering
            • Get image data
            • Detect image
            • Set optimizer learning rate
            Get all kandi verified functions for this library.

            yolov4-tiny-pytorch Key Features

            No Key Features are available at this moment for yolov4-tiny-pytorch.

            yolov4-tiny-pytorch Examples and Code Snippets

            No Code Snippets are available at this moment for yolov4-tiny-pytorch.

            Community Discussions

            No Community Discussions are available at this moment for yolov4-tiny-pytorch.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install yolov4-tiny-pytorch

            You can download it from GitHub.
            You can use yolov4-tiny-pytorch like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            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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