Bladder-Cancer-Stage-Detection
kandi X-RAY | Bladder-Cancer-Stage-Detection Summary
kandi X-RAY | Bladder-Cancer-Stage-Detection Summary
Bladder-Cancer-Stage-Detection is a Python library. Bladder-Cancer-Stage-Detection has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However Bladder-Cancer-Stage-Detection build file is not available. You can download it from GitHub.
Bladder-Cancer-Stage-Detection
Bladder-Cancer-Stage-Detection
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Support
Bladder-Cancer-Stage-Detection has a low active ecosystem.
It has 4 star(s) with 1 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Bladder-Cancer-Stage-Detection is current.
Quality
Bladder-Cancer-Stage-Detection has no bugs reported.
Security
Bladder-Cancer-Stage-Detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Bladder-Cancer-Stage-Detection 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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Bladder-Cancer-Stage-Detection releases are not available. You will need to build from source code and install.
Bladder-Cancer-Stage-Detection has no build file. You will be need to create the build yourself to build the component from source.
Top functions reviewed by kandi - BETA
kandi has reviewed Bladder-Cancer-Stage-Detection and discovered the below as its top functions. This is intended to give you an instant insight into Bladder-Cancer-Stage-Detection implemented functionality, and help decide if they suit your requirements.
- Forward computation
- Compute the bounding boxes for a batch
- Unmap data
- Transforms a batch of bbox into a single dimension
- Forward the prediction
- NMS estimator
- Clip boxes to given image size
- This function transforms the inverse of a box
- Load selective roidb
- Perform a training step
- Plot the training loss histogram
- Downloads images to tarDir
- Sample two grids
- Returns a model
- Create a configuration dictionary from a list
- Clip boxes
- Wrapper for nms
- Inverse transformation of embedding boxes
- Evaluate recall
- Performs a thresholding thresholding
- Parse command line arguments
- Perform RNN on input image
- Forward the RPN layer
- Create a RegionOf Interest Database
- Show test results
- Generate image blob
- Load image index
- Train the model
Get all kandi verified functions for this library.
Bladder-Cancer-Stage-Detection Key Features
No Key Features are available at this moment for Bladder-Cancer-Stage-Detection.
Bladder-Cancer-Stage-Detection Examples and Code Snippets
No Code Snippets are available at this moment for Bladder-Cancer-Stage-Detection.
Community Discussions
No Community Discussions are available at this moment for Bladder-Cancer-Stage-Detection.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Bladder-Cancer-Stage-Detection
You can download it from GitHub.
You can use Bladder-Cancer-Stage-Detection 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 Bladder-Cancer-Stage-Detection 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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