英文:
use the result of YOLOv8 for pyzbar
问题
以下是翻译的代码部分：
我想将来自YOLOv8的结果传递给解码函数，以便从中读取条形码。
我的程序代码是：
model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
results = model.predict(source=frame, show=True, conf=0.70, stream=True, device=0)
decode(results.numpy())
if cv2.waitKey(10) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
当我这样做时，我收到以下错误消息：
AttributeError: 'generator' object has no attribute 'numpy'
此外，我想使用kraken.binarization.nlbin()对帧进行预处理，这是可能的吗？如果可以的话，应该如何操作？
英文:
I want to pass the result from the YOLOv8 to the decode function so that the barcodes are read from it.
My program code is:
model = YOLO("yolov8n.pt")
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
results = model.predict(source=frame, show=True, conf=0.70, stream=True, device=0)
decode(results.numpy())
if cv2.waitKey(10) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
When I do this, I get the following error message:
AttributeError: 'generator' object has no attribute 'numpy'
Additionally I want to preprocess the frame with kraken.binarization.nlbin() is this possible, if so how?
答案1
得分: 0
如果您阅读Ultralytics的预测文档，您会发现返回结果中不包含任何图像。
您需要自定义您的预测器以返回原始图像，以便您可以使用results中存在的边界框来裁剪图像。然后，您可以将裁剪后的图像传递给decode函数：
import cv2
from ultralytics.yolo.engine.model import YOLO
from pyzbar.pyzbar import decode
def on_predict_batch_end(predictor):
# results -> List[batch_size]
path, im, im0s, vid_cap, s = predictor.batch
predictor.results = zip(predictor.results, im0s)
model = YOLO("yolov8n.pt")
model.add_callback("on_predict_batch_end", on_predict_batch_end)
results = model.predict(source="0", show=True, stream=True)
for i, (result, im0) in enumerate(results):
boxes = result.boxes
for box in boxes:
xyxy = box.xyxy[0] # get box coordinates in (top, left, bottom, right) format
t = int(xyxy[0].item())
l = int(xyxy[1].item())
b = int(xyxy[2].item())
r = int(xyxy[3].item())
crop_img = im0[l:r, t:b]
d = decode(crop_img)
print(d)
cv2.imshow('YOLO V8 crop', crop_img)
这给了我以下输出（我手机屏幕上有一个QR码），我已经对其进行了匿名处理：
0: 480x640 2 persons, 1 cell phone, 9.7ms
[Decoded(data=b'https://wa.me/qr/XXXXXXXXXXXXXX', type='QRCODE', rect=Rect(left=105, top=248, width=90, height=95), polygon=[Point(x=105, y=343), Point(x=193, y=341), Point(x=195, y=251), Point(x=111, y=248)], quality=1, orientation=None)]
英文:
If you read the documentation for Ultralytics' predict you will see that return does not contain any image.
You have to customize your predictor to return the original image so that you can use the bboxes present in results in order to crop the image. Then you can pass the crops to decode:
import cv2
from ultralytics.yolo.engine.model import YOLO
from pyzbar.pyzbar import decode
def on_predict_batch_end(predictor):
# results -> List[batch_size]
path, im, im0s, vid_cap, s = predictor.batch
predictor.results = zip(predictor.results, im0s)
model = YOLO("yolov8n.pt")
model.add_callback("on_predict_batch_end", on_predict_batch_end)
results = model.predict(source="0", show=True, stream=True)
for i, (result, im0) in enumerate(results):
boxes = result.boxes
for box in boxes:
xyxy = box.xyxy[0] # get box coordinates in (top, left, bottom, right) format
t = int(xyxy[0].item())
l = int(xyxy[1].item())
b = int(xyxy[2].item())
r = int(xyxy[3].item())
crop_img = im0[l:r, t:b]
d = decode(crop_img)
print(d)
cv2.imshow('YOLO V8 crop', crop_img)
This gives me the following output (I had a QR code on my phone screen) which I anonymized for obvious reasons:
0: 480x640 2 persons, 1 cell phone, 9.7ms
[Decoded(data=b'https://wa.me/qr/XXXXXXXXXXXXXX', type='QRCODE', rect=Rect(left=105, top=248, width=90, height=95), polygon=[Point(x=105, y=343), Point(x=193, y=341), Point(x=195, y=251), Point(x=111, y=248)], quality=1, orientation=None)]
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