mmdetection-mini | mmdetection minimum learning version
kandi X-RAY | mmdetection-mini Summary
kandi X-RAY | mmdetection-mini Summary
mmdetection-mini is a Python library. mmdetection-mini has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.
mmdetection minimum learning version
mmdetection minimum learning version
Support
Quality
Security
License
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Support
mmdetection-mini has a medium active ecosystem.
It has 955 star(s) with 182 fork(s). There are 25 watchers for this library.
It had no major release in the last 6 months.
There are 29 open issues and 21 have been closed. On average issues are closed in 8 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of mmdetection-mini is current.
Quality
mmdetection-mini has 0 bugs and 0 code smells.
Security
mmdetection-mini has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
mmdetection-mini code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
mmdetection-mini is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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mmdetection-mini releases are not available. You will need to build from source code and install.
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 mmdetection-mini and discovered the below as its top functions. This is intended to give you an instant insight into mmdetection-mini implemented functionality, and help decide if they suit your requirements.
- Create a TpImage from bounding boxes
- Check if two boxes overlap
- Get target anchors
- Show position anchor
- Compute soft - weighted cross - validation
- Convert to torch Tensor
- Default tp fp
- Display the results of the image
- Visualize bounding boxes
- Convert a color to a tuple
- Test if x is a string
- Train a model
- Collect environment variables
- Create a progress bar for the given function
- Convert a list of images into a pre - defined format
- Compute the gradient map
- Generate random bounding boxes
- Replace image to TensorFlow
- Backward computation
- Decorator to register a module
- Calculate the target mask
- Convolution function
- Crops an image
- Forward the convolutional function
- Display bounding boxes
- Calculate the loss for the layer
Get all kandi verified functions for this library.
mmdetection-mini Key Features
No Key Features are available at this moment for mmdetection-mini.
mmdetection-mini Examples and Code Snippets
No Code Snippets are available at this moment for mmdetection-mini.
Community Discussions
No Community Discussions are available at this moment for mmdetection-mini.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install mmdetection-mini
You can download it from GitHub.
You can use mmdetection-mini 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.
You can use mmdetection-mini 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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