我正在使用anaconda 3.6进行微小的YOLO物体检测。我正在努力统计由yolo模型实时检测到的对象。如图所示,我需要计算多个类的多个对象。请给我一个演示代码。谢谢
微型YOLO VOC的示例代码如下所示。
亲爱的, 我正在使用anaconda 3.6进行微小的YOLO物体检测。我正在努力统计由yolo模型实时检测到的对象。如图所示,我需要计算多个类的多个对象。请给我一个演示代码。谢谢
微型YOLO VOC的示例代码如下所示。
tfnet = TFNet(options)
colors = [tuple(255 * np.random.rand(3)) for _ in range(10)]
capture = cv2.VideoCapture(0)
capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
while True:
stime = time.time()
ret, frame = capture.read()
if ret:
results = tfnet.return_predict(frame)
for color, result in zip(colors, results):
tl = (result['topleft']['x'], result['topleft']['y'])
br = (result['bottomright']['x'], result['bottomright']['y'])
X1= result['topleft']['x']
Y1= result['topleft']['y']
X2= result['bottomright']['x']
Y2= result['bottomright']['y']
area= (X2-X1)*(Y2-Y1)
area_text = '{}: {:.0f}%'.format(area)
label = result['label']
confidence = result['confidence']
text = '{}: {:.0f}%'.format(label, confidence * 100)
frame = cv2.rectangle(frame, tl, br, color, 5)
frame = cv2.putText(
frame, text, area_text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
cv2.imshow('frame', frame)
print('FPS {:.1f}'.format(1 / (time.time() - stime)))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()
example image for counting multiple object of multiple categories