目录
推理代码，source可以是文件名，路径，
预测可视化：
训练自己的数据集，
训练一段时间报错：dill
解决方法：
推理代码，source可以是文件名，路径，
保存结果：
from ultralytics import YOLOv10# model = YOLOv10.from_pretrained('jameslahm/yolov10{n/s/m/b/l/x}')
# or
# wget https://github.com/THU-MIG/yolov10/releases/download/v1.1/yolov10{n/s/m/b/l/x}.pt
model = YOLOv10('yolov10s.pt')# model.val(data='coco.yaml', batch=256)source = 'http://images.cocodataset.org/val2017/000000039769.jpg'
source = 'F:\data\qijun\dao\pics_re_1'
model.predict(source=source, save=True)预测可视化：
from ultralytics import YOLOv10
import supervision as sv
import cv2MODEL_PATH = 'yolov10n.pt'
IMAGE_PATH = 'dog.jpeg'model = YOLOv10(MODEL_PATH)
image = cv2.imread(IMAGE_PATH)
results = model(source=image, conf=0.25, verbose=False)[0]
detections = sv.Detections.from_ultralytics(results)
box_annotator = sv.BoxAnnotator()category_dict = {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus',6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant',11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat',16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear',22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag',27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard',32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove',36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle',40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl',46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli',51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake',56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table',61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard',67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink',72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors',77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'
}labels = [f"{category_dict[class_id]} {confidence:.2f}"for class_id, confidence in zip(detections.class_id, detections.confidence)
]
annotated_image = box_annotator.annotate(image.copy(), detections=detections, labels=labels
)cv2.imwrite('annotated_dog.jpeg', annotated_image)训练自己的数据集，
原版标签是txt格式
我下载了完整代码，自己修改数据集
https://download.csdn.net/download/qq_38408785/89356134
from ultralytics import YOLOv10if __name__ == '__main__':model = YOLOv10('ultralytics/cfg/models/v10/yolov10n.yaml')model.load('yolov10n.pt') # loading pretrain weightsmodel.train(data='data/NEU-DET.yaml',cache=False,imgsz=640,epochs=200,batch=16,close_mosaic=10,device='0',optimizer='SGD', # using SGDproject='runs/train',name='exp',)
训练一段时间报错：dill库
File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 603, in saveself.save_reduce(obj=obj, *rv)File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 717, in save_reducesave(state)File "D:\ProgramData\miniconda3\envs\py310\lib\site-packages\dill\_dill.py", line 388, in saveStockPickler.save(self, obj, save_persistent_id)File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 560, in savef(self, obj) # Call unbound method with explicit selfFile "D:\ProgramData\miniconda3\envs\py310\lib\site-packages\dill\_dill.py", line 1186, in save_module_dictStockPickler.save_dict(pickler, obj)File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 972, in save_dictself._batch_setitems(obj.items())File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 997, in _batch_setitemssave(k)File "D:\ProgramData\miniconda3\envs\py310\lib\site-packages\dill\_dill.py", line 388, in saveStockPickler.save(self, obj, save_persistent_id)File "D:\ProgramData\miniconda3\envs\py310\lib\pickle.py", line 539, in savepid = self.persistent_id(obj)File "D:\ProgramData\miniconda3\envs\py310\lib\site-packages\torch\serialization.py", line 622, in persistent_idstorage_type = normalize_storage_type(type(obj))File "D:\ProgramData\miniconda3\envs\py310\lib\site-packages\torch\serialization.py", line 226, in normalize_storage_typereturn getattr(torch, storage_type.__name__)
AttributeError: module 'torch' has no attribute 'str'解决方法：
pip install dill -U
升级为dill-0.3.8 后报错没有了。