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---
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)
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