Tensor Flow Object detection API notifications










1















Tensorflow 1.12.0
Python 3.5.0
Windows 10



Hello all, I've created my own object detection model based on tensorflows object detection tutorial. I want to notify by SMS (via a service like twilio) when a object is detected, but I don't want to be notified by every frame of the same object class, instead I'd like to have a delay between text messages of objects i.e. every 5 seconds (at least) between every call. I've looked at threading and timer, but I fear that I'll restart the threading and timer every for call and was wondering if their is a more efficient way via the object detection API to accomplish this task. I know that I can print the actual class detected via



print [category_index.get(value) for index,value in enumerate(classes[0]) if scores[0,index] > 0.5]


in the code



with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
while True:
ret, image_np = cap.read()
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
# Each box represents a part of the image where a particular object was detected.
boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
# Each score represent how level of confidence for each of the objects.
# Score is shown on the result image, together with the class label.
scores = detection_graph.get_tensor_by_name('detection_scores:0')
classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
# Actual detection.
(boxes, scores, classes, num_detections) = sess.run(
[boxes, scores, classes, num_detections],
feed_dict=image_tensor: image_np_expanded)
# Visualization of the results of a detection.
vis_util.visualize_boxes_and_labels_on_image_array(
image_np,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8)

cv2.imshow('object detection', cv2.resize(image_np, (800,600)))
if cv2.waitKey(25) & 0xFF == ord('q'):
cv2.destroyAllWindows()
break


but again, I don't want an overflow of text messages to my phone, and I don't want my script to pause neither.. if any suggestions can be given, I'd appreciate it. Thank you all.










share|improve this question


























    1















    Tensorflow 1.12.0
    Python 3.5.0
    Windows 10



    Hello all, I've created my own object detection model based on tensorflows object detection tutorial. I want to notify by SMS (via a service like twilio) when a object is detected, but I don't want to be notified by every frame of the same object class, instead I'd like to have a delay between text messages of objects i.e. every 5 seconds (at least) between every call. I've looked at threading and timer, but I fear that I'll restart the threading and timer every for call and was wondering if their is a more efficient way via the object detection API to accomplish this task. I know that I can print the actual class detected via



    print [category_index.get(value) for index,value in enumerate(classes[0]) if scores[0,index] > 0.5]


    in the code



    with detection_graph.as_default():
    with tf.Session(graph=detection_graph) as sess:
    while True:
    ret, image_np = cap.read()
    # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
    image_np_expanded = np.expand_dims(image_np, axis=0)
    image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
    # Each box represents a part of the image where a particular object was detected.
    boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
    # Each score represent how level of confidence for each of the objects.
    # Score is shown on the result image, together with the class label.
    scores = detection_graph.get_tensor_by_name('detection_scores:0')
    classes = detection_graph.get_tensor_by_name('detection_classes:0')
    num_detections = detection_graph.get_tensor_by_name('num_detections:0')
    # Actual detection.
    (boxes, scores, classes, num_detections) = sess.run(
    [boxes, scores, classes, num_detections],
    feed_dict=image_tensor: image_np_expanded)
    # Visualization of the results of a detection.
    vis_util.visualize_boxes_and_labels_on_image_array(
    image_np,
    np.squeeze(boxes),
    np.squeeze(classes).astype(np.int32),
    np.squeeze(scores),
    category_index,
    use_normalized_coordinates=True,
    line_thickness=8)

    cv2.imshow('object detection', cv2.resize(image_np, (800,600)))
    if cv2.waitKey(25) & 0xFF == ord('q'):
    cv2.destroyAllWindows()
    break


    but again, I don't want an overflow of text messages to my phone, and I don't want my script to pause neither.. if any suggestions can be given, I'd appreciate it. Thank you all.










    share|improve this question
























      1












      1








      1








      Tensorflow 1.12.0
      Python 3.5.0
      Windows 10



      Hello all, I've created my own object detection model based on tensorflows object detection tutorial. I want to notify by SMS (via a service like twilio) when a object is detected, but I don't want to be notified by every frame of the same object class, instead I'd like to have a delay between text messages of objects i.e. every 5 seconds (at least) between every call. I've looked at threading and timer, but I fear that I'll restart the threading and timer every for call and was wondering if their is a more efficient way via the object detection API to accomplish this task. I know that I can print the actual class detected via



      print [category_index.get(value) for index,value in enumerate(classes[0]) if scores[0,index] > 0.5]


      in the code



      with detection_graph.as_default():
      with tf.Session(graph=detection_graph) as sess:
      while True:
      ret, image_np = cap.read()
      # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
      image_np_expanded = np.expand_dims(image_np, axis=0)
      image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
      # Each box represents a part of the image where a particular object was detected.
      boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
      # Each score represent how level of confidence for each of the objects.
      # Score is shown on the result image, together with the class label.
      scores = detection_graph.get_tensor_by_name('detection_scores:0')
      classes = detection_graph.get_tensor_by_name('detection_classes:0')
      num_detections = detection_graph.get_tensor_by_name('num_detections:0')
      # Actual detection.
      (boxes, scores, classes, num_detections) = sess.run(
      [boxes, scores, classes, num_detections],
      feed_dict=image_tensor: image_np_expanded)
      # Visualization of the results of a detection.
      vis_util.visualize_boxes_and_labels_on_image_array(
      image_np,
      np.squeeze(boxes),
      np.squeeze(classes).astype(np.int32),
      np.squeeze(scores),
      category_index,
      use_normalized_coordinates=True,
      line_thickness=8)

      cv2.imshow('object detection', cv2.resize(image_np, (800,600)))
      if cv2.waitKey(25) & 0xFF == ord('q'):
      cv2.destroyAllWindows()
      break


      but again, I don't want an overflow of text messages to my phone, and I don't want my script to pause neither.. if any suggestions can be given, I'd appreciate it. Thank you all.










      share|improve this question














      Tensorflow 1.12.0
      Python 3.5.0
      Windows 10



      Hello all, I've created my own object detection model based on tensorflows object detection tutorial. I want to notify by SMS (via a service like twilio) when a object is detected, but I don't want to be notified by every frame of the same object class, instead I'd like to have a delay between text messages of objects i.e. every 5 seconds (at least) between every call. I've looked at threading and timer, but I fear that I'll restart the threading and timer every for call and was wondering if their is a more efficient way via the object detection API to accomplish this task. I know that I can print the actual class detected via



      print [category_index.get(value) for index,value in enumerate(classes[0]) if scores[0,index] > 0.5]


      in the code



      with detection_graph.as_default():
      with tf.Session(graph=detection_graph) as sess:
      while True:
      ret, image_np = cap.read()
      # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
      image_np_expanded = np.expand_dims(image_np, axis=0)
      image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
      # Each box represents a part of the image where a particular object was detected.
      boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
      # Each score represent how level of confidence for each of the objects.
      # Score is shown on the result image, together with the class label.
      scores = detection_graph.get_tensor_by_name('detection_scores:0')
      classes = detection_graph.get_tensor_by_name('detection_classes:0')
      num_detections = detection_graph.get_tensor_by_name('num_detections:0')
      # Actual detection.
      (boxes, scores, classes, num_detections) = sess.run(
      [boxes, scores, classes, num_detections],
      feed_dict=image_tensor: image_np_expanded)
      # Visualization of the results of a detection.
      vis_util.visualize_boxes_and_labels_on_image_array(
      image_np,
      np.squeeze(boxes),
      np.squeeze(classes).astype(np.int32),
      np.squeeze(scores),
      category_index,
      use_normalized_coordinates=True,
      line_thickness=8)

      cv2.imshow('object detection', cv2.resize(image_np, (800,600)))
      if cv2.waitKey(25) & 0xFF == ord('q'):
      cv2.destroyAllWindows()
      break


      but again, I don't want an overflow of text messages to my phone, and I don't want my script to pause neither.. if any suggestions can be given, I'd appreciate it. Thank you all.







      tensorflow timer object-detection






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 15 '18 at 18:51









      carlgausscarlgauss

      163




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