FSCE | repo contains the implementation of our state-of-the-art

by MegviiDetection Python Version: Current License: Apache-2.0

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

kandi X-RAY | FSCE Summary

FSCE is a Python library. FSCE 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 repo contains the implementation of our state-of-the-art fewshot object detector, described in our CVPR 2021 paper, FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding. FSCE is built upon the codebase FsDet v0.1, which released by an ICML 2020 paper Frustratingly Simple Few-Shot Object Detection.

Support

Quality

Security

License

Reuse

Support

FSCE has a low active ecosystem.

It has 104 star(s) with 15 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 14 open issues and 20 have been closed. On average issues are closed in 8 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of FSCE is current.

Quality

FSCE has no bugs reported.

Security

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

License

FSCE is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

FSCE 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, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed FSCE and discovered the below as its top functions. This is intended to give you an instant insight into FSCE implemented functionality, and help decide if they suit your requirements.

Convert C2 layer weights to C2 weights .
Load filtered vocabulary .
Return configuration for COCO detection .
Evaluate a set of detections .
Aligns two dictionaries .
Load data from a coco . json file .
Find top - k proposals for prediction .
Register all Pascal vocab .
Build resnet backbone .
Load Lvis data from a Lvis API .

Get all kandi verified functions for this library.

FSCE Key Features

No Key Features are available at this moment for FSCE.

FSCE Examples and Code Snippets

No Code Snippets are available at this moment for FSCE.

Community Discussions

No Community Discussions are available at this moment for FSCE.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install FSCE

FsDet is built on Detectron2. But you don't need to build detectron2 seperately as this codebase is self-contained. You can follow the instructions below to install the dependencies and build FsDet. FSCE functionalities are implemented as classand .py scripts in FsDet which therefore requires no extra build efforts. Note: you may need to rebuild FsDet after reinstalling a different build of PyTorch.
Linux with Python >= 3.6
PyTorch >= 1.3
torchvision that matches the PyTorch installation
Dependencies: pip install -r requirements.txt
pycocotools: pip install cython; pip install 'git+https://github.com/cocodataset/cocoapi.git#subdirectory=PythonAPI'
fvcore: pip install 'git+https://github.com/facebookresearch/fvcore'
OpenCV, optional, needed by demo and visualization pip install opencv-python
GCC >= 4.9

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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