车牌检测-基于YOLOv10训练自定义车牌检测数据实现车牌检测算法-附流程教程-优质项目实战.zip

 ### Environment Setup ##### This code is tested on python 3.9 ##### Video tutorial: https://youtu.be/Dmv4EVBuCTQ Step -1 : git clone https://github.com/THU-MIG/yolov10.git Step -2 : cd yolov10 Step -3 : pip install . Step -4 : Download yolov10 pretrained weights from official repo (https://github.com/THU-MIG/yolov10) Step -5 : Test Pretrained YOLOv10 model using this command: ##### !yolo task=detect mode=predict conf=0.25 save=True model=../weights/yolov10n.pt source=test_images/1.jpg ##### Train Custom model: 1- Custom dataset is required for training the model. Sample dataset is in "custom_dataset" folder, Your dataset should have the same format. 2- Make changes in in custom_data.yaml file as per your dataset ##### 3. Train model using this command: !yolo task=detect mode=train epochs=100 batch=16 plots=True model=weights/yolov10n.pt data=custom_data.yaml ##### 4. Inference using custom trained model: !yolo task=detect mode=predict conf=0.25 save=True model=runs/detect/train/weights/best.pt source=test_images_1/veh2.jpg