我应该添加些什么,以便当系统检测到某些特定对象时会发出警报声?

时间:2019-09-28 16:45:12

标签: tensorflow object-detection-api

我已经使用网络摄像头完成了对象检测api,系统已成功运行了检测到的对象,现在我想添加,当系统检测到某些特定对象时,它将播放差异警报声音

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)
    #if xxxxx:
    #    alert.play()
    #else:
    #    pass
    # 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

我的系统是自动检测危险武器,当我的系统检测到“枪”或“刀”时,它将通过声音警报来提醒安全。

2 个答案:

答案 0 :(得分:0)

对于Windows

import winsound

winsound.PlaySound("sound_file.wav", FLAG)

或只是哔哔声

import winsound

dur = 500 # as millisecond
freq = 2000 # sound frequency
winsound.Beep(freq, dur)

您可以检查文件 https://docs.python.org/3.7/library/winsound.html

用于其他操作系统(Linux,Mac等)

import os

os.system("sound_file.wav&")

答案 1 :(得分:0)

插入循环

          Date   Planned_x  Actuals     ...       C2P (%)  Planned_y       Delta
766 2019-09-19  284.000000    439.0     ...           NaN        NaN -155.000000
767 2019-09-20  284.000000    469.0     ...           NaN        NaN -185.000000
768 2019-09-21  260.000000    240.0     ...           NaN        NaN   20.000000
769 2019-09-22  305.000000    229.0     ...           NaN        NaN   76.000000
770 2019-09-23  351.000000    225.0     ...      0.533391        NaN  126.000000
771 2019-09-24  387.353430      1.0     ...           NaN        NaN  386.353430
772 2019-09-25  444.317519    152.0     ...           NaN        NaN  292.317519
773 2019-09-26  475.557830    300.0     ...           NaN        NaN  175.557830
774 2019-09-27  404.524517    150.0     ...           NaN        NaN  254.524517
775 2019-09-28  355.303705    550.0     ...           NaN        NaN -194.696295