| license: cc-by-4.0 | |
| tags: | |
| - image-classification | |
| - image-segmentation | |
| - defect-detection | |
| - pytorch | |
| - unet++ | |
| - resnet | |
| - dqn | |
| language: | |
| - zh | |
| # 汽车漆面缺陷检测模型 | |
| 基于深度学习的汽车漆面缺陷检测系统，包含三个核心模块。 | |
| ## 模型文件 | |
| | 模型 | 文件 | 大小 | 用途 | | |
| |------|------|------|------| | |
| | DQN图像增强 | task1_dqn/dqn_final.pth | ~987MB | 强化学习图像增强 | | |
| | UNet++分割 | task2_unetpp/best_model.pth | ~105MB | 缺陷区域分割 (IoU=0.884) | | |
| | ResNet分类 | task3_classification/best_model.pth | ~283MB | 缺陷类型分类 (Acc=96.3%) | | |
| ## 下载方法 | |
| ```python | |
| from huggingface_hub import hf_hub_download | |
| # 下载分割模型 | |
| model_path = hf_hub_download( | |
| repo_id="TrainingCat/car-paint-defect-detection", | |
| filename="task2_unetpp/best_model.pth" | |
| ) | |
| ``` | |
| 或使用命令行: | |
| ```bash | |
| huggingface-cli download TrainingCat/car-paint-defect-detection --local-dir models/ | |
| ``` | |
| ## 数据集 | |
| [Roboflow Car Paint Defect Dataset](https://universe.roboflow.com/poli-h7nww/final-year-car-paint-defect/dataset/1) | |