复现 InceptionNet
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help-wanted
- Dominant language
- Python
- Stars
- 306
- Forks
- 96
- PR merge metrics
- No merged PRs in 30d
Description
任务描述
- 复现 InceptionNet ，训练正常收敛，验收指标符合预期，并将代码提交到 offical/vision/classification/models 下
目标
- 数据集ImageNet
- 准确率和论文一致或更高
- 脚本可以完整完成训练步骤
- 提供训练后的权重文件
- 提交至 https://github.com/MegEngine/Hub
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing structure under offical/vision/classification/models and the repository’s MegEngine model conventions. Implement an InceptionNet reproduction using ImageNet, then verify that training completes and reaches the paper’s accuracy target. Done includes the training script, trained weight file, and submission to MegEngine/Hub.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100