yolov8 裁剪检测结果
- 1. 基础
- 2. 图片批量裁剪
- 2.1 检测裁剪
- 2.2 分割裁剪
- 3. 视频裁剪
- 3.1 检测裁剪
- 3.2 分割裁剪
- 3.3 实时裁剪
- 4. 源码
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 os
model = 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 = 0
for 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 += 1
crop_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'):
break
cv2.destroyAllWindows()
2.2 分割裁剪
from ultralytics import YOLO
import cv2
import os
model = 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 = 0
for 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 += 1
crop_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'):
break
cv2.destroyAllWindows()
3. 视频裁剪
3.1 检测裁剪
from ultralytics import YOLO
import cv2
import os
model = YOLO("yolov8n.pt")
names = model.names
cap = 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.")
break
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 += 1
crop_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'):
break
cap.release()
cv2.destroyAllWindows()
结果：
3.2 分割裁剪
from ultralytics import YOLO
import cv2
import os
model = YOLO("yolov8n-seg.pt")
names = model.names
cap = 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.")
break
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 += 1
crop_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'):
break
cap.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
