车辆检测数据集模型计数+车牌定位+车牌数据识别的融合技术.zip

车辆检测数据车牌定位系统车牌识别技术

基于pytorch深度学习框架，实用开源模型yolov4实现模板检测与yolov5实现车牌检测与LPRNet实现车牌检测基于pytorch深度学习框架，实用开源模型yolov4实现模板检测与yolov5实现车牌检测与LPRNet实现车牌检测基于win10系统，实用anaconda配置python环境，在anaconda里面下载vscode对项目进行编辑，基于pytorch深度学习框架，实用开源模型yolov4实现模板检测与yolov5实现车牌检测与LPRNet实现车牌检测基于pytorch深度学习框架，实用开源模型yolov4实现模板检测与yolov5实现车牌检测与LPRNet实现车牌检测基于win10系统，实用anaconda配置python环境，在anaconda里面下载vscode对项目进行编辑

文件下载

资源详情

[{"title":"（ 59 个子文件 11.44MB ）车辆检测数据集模型计数+车牌定位+车牌数据识别的融合技术.zip","children":[{"title":"car-master","children":[{"title":"models","children":[{"title":"common.py <span style='color:#111;'> 3.57KB </span>","children":null,"spread":false},{"title":"LPRNet.py <span style='color:#111;'> 4.02KB </span>","children":null,"spread":false},{"title":"yolo.py <span style='color:#111;'> 10.47KB </span>","children":null,"spread":false},{"title":"hub","children":[{"title":"yolov3-spp.yaml <span style='color:#111;'> 1.63KB </span>","children":null,"spread":false},{"title":"yolov5-fpn.yaml <span style='color:#111;'> 1.34KB </span>","children":null,"spread":false},{"title":"yolov5-panet.yaml <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false}],"spread":true},{"title":"yolov5s.yaml <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"experimental.cpython-36.pyc <span style='color:#111;'> 6.37KB </span>","children":null,"spread":false},{"title":"yolo.cpython-36.pyc <span style='color:#111;'> 8.13KB </span>","children":null,"spread":false},{"title":"common.cpython-36.pyc <span style='color:#111;'> 5.45KB </span>","children":null,"spread":false},{"title":"LPRNet.cpython-36.pyc <span style='color:#111;'> 3.09KB </span>","children":null,"spread":false}],"spread":true},{"title":"yolo1.py <span style='color:#111;'> 13.25KB </span>","children":null,"spread":false},{"title":"yolov5x.yaml <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"yolov5l.yaml <span style='color:#111;'> 1.54KB </span>","children":null,"spread":false},{"title":"spinenet.py <span style='color:#111;'> 4.76KB </span>","children":null,"spread":false},{"title":"export.py <span style='color:#111;'> 2.83KB </span>","children":null,"spread":false},{"title":"yolov5m.yaml <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"experimental.py <span style='color:#111;'> 5.35KB </span>","children":null,"spread":false}],"spread":false},{"title":"yolo.py <span style='color:#111;'> 16.74KB </span>","children":null,"spread":false},{"title":"nets","children":[{"title":"yolo4.py <span style='color:#111;'> 6.77KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"yolo_training.cpython-36.pyc <span style='color:#111;'> 11.39KB </span>","children":null,"spread":false},{"title":"yolo4.cpython-36.pyc <span style='color:#111;'> 4.38KB </span>","children":null,"spread":false},{"title":"CSPdarknet.cpython-36.pyc <span style='color:#111;'> 4.41KB </span>","children":null,"spread":false}],"spread":true},{"title":"CSPdarknet.py <span style='color:#111;'> 7.09KB </span>","children":null,"spread":false},{"title":"yolo_training.py <span style='color:#111;'> 23.49KB </span>","children":null,"spread":false}],"spread":true},{"title":"__pycache__","children":[{"title":"yolo.cpython-36.pyc <span style='color:#111;'> 7.80KB </span>","children":null,"spread":false}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 9.37KB </span>","children":null,"spread":false},{"title":"detect.py <span style='color:#111;'> 8.34KB </span>","children":null,"spread":false},{"title":"model_data","children":[{"title":"simhei.ttf <span style='color:#111;'> 9.30MB </span>","children":null,"spread":false},{"title":"yolo_anchors.txt <span style='color:#111;'> 85B </span>","children":null,"spread":false},{"title":"car_classes.txt <span style='color:#111;'> 217B </span>","children":null,"spread":false},{"title":"coco_classes.txt <span style='color:#111;'> 705B </span>","children":null,"spread":false},{"title":"voc_classes.txt <span style='color:#111;'> 153B </span>","children":null,"spread":false}],"spread":true},{"title":".gitignore <span style='color:#111;'> 1.30KB </span>","children":null,"spread":false},{"title":"inference","children":[{"title":"images","children":[{"title":"3.jpg <span style='color:#111;'> 686.14KB </span>","children":null,"spread":false},{"title":"1.png <span style='color:#111;'> 202.43KB </span>","children":null,"spread":false},{"title":"2.png <span style='color:#111;'> 609.11KB </span>","children":null,"spread":false},{"title":"k.png <span style='color:#111;'> 794.26KB </span>","children":null,"spread":false}],"spread":true},{"title":"output","children":[{"title":"cv.mp4 <span style='color:#111;'> 1.56MB </span>","children":null,"spread":false},{"title":"3.jpg <span style='color:#111;'> 145.74KB </span>","children":null,"spread":false},{"title":"1.png <span style='color:#111;'> 154.35KB </span>","children":null,"spread":false},{"title":"2.png <span style='color:#111;'> 682.13KB </span>","children":null,"spread":false},{"title":"k.png <span style='color:#111;'> 873.15KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"weights","children":[{"title":".keep <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"download_weights.sh <span style='color:#111;'> 244B </span>","children":null,"spread":false},{"title":"Final_LPRNet_model.pth <span style='color:#111;'> 1.72MB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 4.03KB </span>","children":null,"spread":false},{"title":"utils","children":[{"title":"grneral.py <span style='color:#111;'> 54.35KB </span>","children":null,"spread":false},{"title":"utils.py <span style='color:#111;'> 51.62KB </span>","children":null,"spread":false},{"title":"utils_1.py <span style='color:#111;'> 15.47KB </span>","children":null,"spread":false},{"title":"__pycache__","children":[{"title":"torch_utils.cpython-36.pyc <span style='color:#111;'> 8.67KB </span>","children":null,"spread":false},{"title":"google_utils.cpython-36.pyc <span style='color:#111;'> 2.33KB </span>","children":null,"spread":false},{"title":"datasets.cpython-36.pyc <span style='color:#111;'> 25.09KB </span>","children":null,"spread":false},{"title":"utils.cpython-36.pyc <span style='color:#111;'> 38.59KB </span>","children":null,"spread":false},{"title":"utils_1.cpython-36.pyc <span style='color:#111;'> 6.36KB </span>","children":null,"spread":false}],"spread":false},{"title":"datasets.py <span style='color:#111;'> 36.36KB </span>","children":null,"spread":false},{"title":"activations.py <span style='color:#111;'> 1.62KB </span>","children":null,"spread":false},{"title":"torch_utils.py <span style='color:#111;'> 8.89KB </span>","children":null,"spread":false},{"title":"google_utils.py <span style='color:#111;'> 4.28KB </span>","children":null,"spread":false}],"spread":true}],"spread":false},{"title":"文件夹1","children":null,"spread":false}],"spread":true}]

评论信息

其他资源

免责申明

【只为小站】的资源来自网友分享，仅供学习研究，请务必在下载后24小时内给予删除，不得用于其他任何用途，否则后果自负。基于互联网的特殊性，【只为小站】无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查；无论【只为小站】经营者是否已进行审查，用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见版权及免责申明