1. 基础

本项目是在 Windows+YOLOV8环境配置 的基础上实现的
思路：将检测得到的物体边框提取，然后边框裁剪原图，并把裁剪后的结果保存在文件夹

2. 图片批量裁剪

2.1 检测裁剪

from ultralytics import YOLO
import cv2
import osmodel = YOLO("yolov8n.pt")
names = model.names# 获取文件夹中所有图像文件的路径
image_files = [os.path.join("./ultralytics/assets", f) for f in os.listdir("./ultralytics/assets") if f.endswith(".jpg") or f.endswith(".png")]
crop_dir_name = "ultralytics_crop"
if not os.path.exists(crop_dir_name):os.mkdir(crop_dir_name)idx = 0for image_file in image_files:# 读取图像im0 = cv2.imread(image_file)results = model.predict(im0, show=False)boxes = results[0].boxes.xyxy.cpu().tolist()clss = results[0].boxes.cls.cpu().tolist()annotated_frame = results[0].plot()if boxes is not None:for box, cls in zip(boxes, clss):idx += 1crop_obj = im0[int(box[1]):int(box[3]), int(box[0]):int(box[2])]cv2.imwrite(os.path.join(crop_dir_name, str(idx)+".png"), crop_obj)cv2.imshow("ultralytics", annotated_frame)if cv2.waitKey(1) & 0xFF == ord('q'):breakcv2.destroyAllWindows()

2.2 分割裁剪

from ultralytics import YOLO
import cv2
import osmodel = YOLO("yolov8n-seg.pt")
names = model.names# 获取文件夹中所有图像文件的路径
image_files = [os.path.join("./ultralytics/assets", f) for f in os.listdir("./ultralytics/assets") if f.endswith(".jpg") or f.endswith(".png")]
crop_dir_name = "ultralytics_crop"
if not os.path.exists(crop_dir_name):os.mkdir(crop_dir_name)idx = 0for image_file in image_files:# 读取图像im0 = cv2.imread(image_file)results = model.predict(im0, show=False)boxes = results[0].boxes.xyxy.cpu().tolist()clss = results[0].boxes.cls.cpu().tolist()annotated_frame = results[0].plot()if boxes is not None:for box, cls in zip(boxes, clss):idx += 1crop_obj = annotated_frame[int(box[1]):int(box[3]), int(box[0]):int(box[2])]cv2.imwrite(os.path.join(crop_dir_name, str(idx)+".png"), crop_obj)cv2.imshow("ultralytics", annotated_frame)if cv2.waitKey(1) & 0xFF == ord('q'):breakcv2.destroyAllWindows()

3. 视频裁剪

3.1 检测裁剪

from ultralytics import YOLO
import cv2
import osmodel = YOLO("yolov8n.pt")
names = model.namescap = cv2.VideoCapture("./ultralytics/assets/a2.mp4")
assert cap.isOpened(), "Error reading video file"crop_dir_name = "ultralytics_crop"
if not os.path.exists(crop_dir_name):os.mkdir(crop_dir_name)idx = 0
while cap.isOpened():success, im0 = cap.read()if not success:print("Video frame is empty or video processing has been successfully completed.")breakresults = model.predict(im0, show=False)boxes = results[0].boxes.xyxy.cpu().tolist()clss = results[0].boxes.cls.cpu().tolist()annotated_frame = results[0].plot()if boxes is not None:for box, cls in zip(boxes, clss):idx += 1crop_obj = im0[int(box[1]):int(box[3]), int(box[0]):int(box[2])]cv2.imwrite(os.path.join(crop_dir_name, str(idx)+".png"), crop_obj)cv2.imshow("ultralytics", annotated_frame)if cv2.waitKey(1) & 0xFF == ord('q'):breakcap.release()
cv2.destroyAllWindows()

结果：

3.2 分割裁剪

from ultralytics import YOLO
import cv2
import osmodel = YOLO("yolov8n-seg.pt")
names = model.namescap = cv2.VideoCapture("./ultralytics/assets/a2.mp4")
assert cap.isOpened(), "Error reading video file"crop_dir_name = "ultralytics_crop"
if not os.path.exists(crop_dir_name):os.mkdir(crop_dir_name)idx = 0
while cap.isOpened():success, im0 = cap.read()if not success:print("Video frame is empty or video processing has been successfully completed.")breakresults = model.predict(im0, show=False)boxes = results[0].boxes.xyxy.cpu().tolist()clss = results[0].boxes.cls.cpu().tolist()annotated_frame = results[0].plot()if boxes is not None:for box, cls in zip(boxes, clss):idx += 1crop_obj = annotated_frame[int(box[1]):int(box[3]), int(box[0]):int(box[2])]cv2.imwrite(os.path.join(crop_dir_name, str(idx)+".png"), crop_obj)cv2.imshow("ultralytics", annotated_frame)if cv2.waitKey(1) & 0xFF == ord('q'):breakcap.release()
cv2.destroyAllWindows()

结果：

3.3 实时裁剪

如果想打开摄像头实时裁剪只许把视频裁剪中的

cap = cv2.VideoCapture("./ultralytics/assets/a2.mp4")

改为

cap = cv2.VideoCapture(0)

即可

4. 源码

可以去 Windows+YOLOV8环境配置 下载源码，然后在主目录创建一个py文件，把上边代码贴进去运行即可