facebookresearch/maskrcnn-benchmark

Plan for various backbone networks

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#100 opened on Nov 2, 2018

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 (6 comments) (0 reactions) (0 assignees)Python (9,161 stars) (2,574 forks)batch import
contributions welcomegood first issue

Description

🚀 Feature

Support for various backbones like VGG, ResNeXT, etc.

Motivation

Currently, only ResNet and FPN backbones are supported. It would be useful if other backbones like VGG Net or ResNeXT etc. are also included.

Contributor guide

Tech stack
pythonpytorch
Domain
machine learningai
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
PyTorch basicsunderstanding of backbone architecturesfamiliarity with maskrcnn benchmark codebase
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30
Research direction
Examine the existing backbone implementations in the maskrcnn benchmark repository (e.g., resnet.py, fpn.py) to understand the interface and how new backbones can be added. Review the comments in the issue for any discussion on preferred implementation approach. Consider implementing VGG or ResNeXt backbone following the pattern of ResNet, and ensure compatibility with the existing ROI heads and feature pyramid network.