我已经用网络摄像头完成了目标检测。我可以知道,当系统检测到某些特定对象(枪/刀)时,系统将使用警报声音向用户发出警报
祝你今天愉快
我已经导入了pygame作为我的音响系统,但是当我将结果和pygame结合起来时,它就不起作用了
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
detection_scores =detection_graph.get_tensor_by_name('detection_scores:0')
detection_class=detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
video = cv2.VideoCapture(0)
ret = video.set(3,1280)
ret = video.set(4,720)
while(True):
# Acquire frame and expand frame dimensions to have shape: [1, None, None, 3]
# i.e. a single-column array, where each item in the column has the pixel RGB value
ret, frame = video.read()
frame_expanded = np.expand_dims(frame, axis=0)
# Perform the actual detection by running the model with the image as input
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_classes, num_detections],
feed_dict={image_tensor: frame_expanded})
# Draw the results of the detection (aka 'visulaize the results')
vis_util.visualize_boxes_and_labels_on_image_array(
frame,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8,
min_score_thresh=0.60)
# All the results have been drawn on the frame, so it's time to display it.
cv2.imshow('Object detector', frame)
# Press 'q' to quit
if cv2.waitKey(1) == ord('q'):
break
目前没有回答
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