Few-shot-Object-Detection-via-Feature-Reweighting | remake version for the original code
kandi X-RAY | Few-shot-Object-Detection-via-Feature-Reweighting Summary
kandi X-RAY | Few-shot-Object-Detection-via-Feature-Reweighting Summary
Few-shot-Object-Detection-via-Feature-Reweighting is a Python library. Few-shot-Object-Detection-via-Feature-Reweighting has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
This repo is the remake version for the original code of .
This repo is the remake version for the original code of .
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Quality
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Support
Few-shot-Object-Detection-via-Feature-Reweighting has a low active ecosystem.
It has 9 star(s) with 0 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 2 have been closed. On average issues are closed in 68 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Few-shot-Object-Detection-via-Feature-Reweighting is current.
Quality
Few-shot-Object-Detection-via-Feature-Reweighting has 0 bugs and 0 code smells.
Security
Few-shot-Object-Detection-via-Feature-Reweighting has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Few-shot-Object-Detection-via-Feature-Reweighting code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Few-shot-Object-Detection-via-Feature-Reweighting does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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Few-shot-Object-Detection-via-Feature-Reweighting 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 Few-shot-Object-Detection-via-Feature-Reweighting and discovered the below as its top functions. This is intended to give you an instant insight into Few-shot-Object-Detection-via-Feature-Reweighting implemented functionality, and help decide if they suit your requirements.
- Calculate valid images
- Performs the forward computation
- Load weights from a weight file
- Duplicate x1 and x2
- Create a network from a list of blocks
- Create dynamic convolutional layer
- Forward computation
- Builds the targets
- Compute the intersection between two boxes
- Forward pass through the model
- This function runs the python script
- Train model
- Save weights to file
- Forward computation
- Detect the image
- Generate label1 csv files
- Plot boxes
- Loads a video
- Run detection on an image
- Evaluate a darknet image
- Detects the image using Darknet
- Detect boxes using darknet
- Parse a cfg file
- Run darknet detection
- Generate trainvaldict
- Generate train dictionary
- Generate few images
Get all kandi verified functions for this library.
Few-shot-Object-Detection-via-Feature-Reweighting Key Features
No Key Features are available at this moment for Few-shot-Object-Detection-via-Feature-Reweighting.
Few-shot-Object-Detection-via-Feature-Reweighting Examples and Code Snippets
No Code Snippets are available at this moment for Few-shot-Object-Detection-via-Feature-Reweighting.
Community Discussions
No Community Discussions are available at this moment for Few-shot-Object-Detection-via-Feature-Reweighting.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Few-shot-Object-Detection-via-Feature-Reweighting
You can download it from GitHub.
You can use Few-shot-Object-Detection-via-Feature-Reweighting 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 Few-shot-Object-Detection-via-Feature-Reweighting 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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