Tensor Flow Object detection API notifications
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
add a comment |
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
add a comment |
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
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
tensorflow timer object-detection
asked Nov 15 '18 at 18:51
carlgausscarlgauss
163
163
add a comment |
add a comment |
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