Resnet34 as backbone for segmentation models

描述

贡献者指南

技术栈

python

领域

machine learning

议题类型

feature

难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。

3

预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。

1-2 days

活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。

stale

清晰度议题是否清楚说明期望改动、验收标准和下一步。

mostly clear

前置要求

Python programmingPyTorch basicsUnderstanding of ResNet architecture

新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。

55

研究方向

First, study how ResNet50 backbone was integrated into segmentation models in this repo (likely in torchvision/models/segmentation/backbone.py). Look for the existing FCN and DeepLab implementations to understand the pattern for adding a new backbone. Then, implement ResNet34 following similar steps: define the backbone, add it to the model registry, and update the weight loading logic if applicable. Check the issue comments for any additional guidance or unresolved questions.