ResNet50 图像分类训练全流程代码(Notebook + 完整注释)-基于 PyTorch 的工程化实战示例

上传者: 43679228 | 上传时间: 2025-12-31 16:59:33 | 文件大小: 83.58MB | 文件类型: ZIP
# ResNet50 图像分类训练 Demo(Notebook) 本项目提供一个 **基于 PyTorch 的 ResNet50 图像分类完整示例**,适合作为: - 初学者理解 ResNet50 的入门模板 - 实战项目的起点代码 - Notebook 可视化训练参考 --- ## 项目结构 02_resnet50_image_classification/ ├── resnet50_demo.ipynb ├── model.py ├── sample_data/ │ ├── class1/ │ └── class2/ ├── runs/ ├── requirements.txt └── README.md --- ## 环境要求 - Python ≥ 3.8 - PyTorch 1.13.1 - torchvision 0.14.1 建议使用 Conda 创建独立环境。 --- ## 快速开始 ```bash pip install -r requirements.txt jupyter notebook --- ## 数据格式说明 采用 torchvision ImageFolder 结构: sample_data/ ├── cat/ │ ├── 001.jpg │ └── 002.jpg └── dog/ ├── 001.jpg └── 002.jpg --- ## 说明 本项目为教学与模板用途,训练参数刻意设置较小, 方便快速跑通流程。 欢迎在此基础上进行二次开发。

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