71 lines
2.1 KiB
Markdown
71 lines
2.1 KiB
Markdown
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## 车辆识别系统
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**目前支持车辆检测+车牌检测识别**
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环境要求: python >=3.6 pytorch >=1.7
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#### **图片测试demo:**
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```
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python Car_recognition.py --detect_model weights/detect.pt --rec_model weights/plate_rec_color.pth --image_path imgs --output result
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```
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测试文件夹imgs，结果保存再 result 文件夹中
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## **检测训练**
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1. **下载数据集：** [datasets](https://pan.baidu.com/s/1YSURJvo4v1N5x7NVsxEA_Q) 提取码：3s0j 数据从CCPD和CRPD数据集中选取并转换的
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数据集格式为yolo格式：
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```
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label x y w h pt1x pt1y pt2x pt2y pt3x pt3y pt4x pt4y
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```
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关键点依次是（左上，右上，右下，左下）
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坐标都是经过归一化，x,y是中心点除以图片宽高，w,h是框的宽高除以图片宽高，ptx，pty是关键点坐标除以宽高
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车辆标注不需要关键点 关键点全部置为-1即可
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2. **修改 data/widerface.yaml train和val路径,换成你的数据路径**
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```
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train: /your/train/path #修改成你的路径
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val: /your/val/path #修改成你的路径
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# number of classes
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nc: 3 #这里用的是3分类，0 单层车牌 1 双层车牌 2 车辆
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# class names
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names: [ 'single_plate','double_plate','Car']
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```
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3. **训练**
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```
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python3 train.py --data data/plateAndCar.yaml --cfg models/yolov5n-0.5.yaml --weights weights/detect.pt --epoch 250
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```
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结果存在run文件夹中
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## **车牌识别训练**
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车牌识别训练链接如下：
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[车牌识别训练](https://github.com/we0091234/crnn_plate_recognition)
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## References
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* [https://github.com/we0091234/Chinese_license_plate_detection_recognition](https://github.com/we0091234/Chinese_license_plate_detection_recognition)
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* [https://github.com/deepcam-cn/yolov5-face](https://github.com/deepcam-cn/yolov5-face)
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* [https://github.com/meijieru/crnn.pytorch](https://github.com/meijieru/crnn.pytorch)
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## TODO
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车型，车辆颜色，品牌等。
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## 联系
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**有问题可以提issues 或者加qq群 823419837 询问**
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