tensorflow object detection API on Colab2019 Community Moderator ElectionTensorflow: how to save/restore a model?TensorFlow not found using pipSimple Feedforward Neural Network with TensorFlow won't learntensorflow object detection API(Calculate Car speeds.)Tensorflow object detection API test errorTensorflow object detection gives No module named 'deployment'Tensorflow Object Detection API ValueError: No variables to saveTensorflow Object-detection apiTensorflow: Does object detection API returns detected object idtensorflow object detection in google colab
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tensorflow object detection API on Colab
2019 Community Moderator ElectionTensorflow: how to save/restore a model?TensorFlow not found using pipSimple Feedforward Neural Network with TensorFlow won't learntensorflow object detection API(Calculate Car speeds.)Tensorflow object detection API test errorTensorflow object detection gives No module named 'deployment'Tensorflow Object Detection API ValueError: No variables to saveTensorflow Object-detection apiTensorflow: Does object detection API returns detected object idtensorflow object detection in google colab
I tried running tensorflow object detection API on Colab according to here.
However, such an error occurred How can I solve it?
I tried step1.2.3.4.
They maybe run.
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
# Definite input and output Tensors for detection_graph
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.
detection_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.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
for image_path in TEST_IMAGE_PATHS:
image = Image.open(image_path)
# the array based representation of the image will be used later in order to prepare the
# result image with boxes and labels on it.
image_np = load_image_into_numpy_array(image)
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
# Actual detection.
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_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)
plt.figure(figsize=IMAGE_SIZE)
plt.imshow(image_np)
The error I receive is:
NameError
Traceback (most recent call last)
<ipython-input-24-7493eea60222> in <module>()
10 detection_classes =
detection_graph.get_tensor_by_name('detection_classes:0')
11 num_detections =
detection_graph.get_tensor_by_name('num_detections:0')
---> 12 for image_path in TEST_IMAGE_PATHS:
13 image = Image.open(image_path)
14 # the array based representation of the image will be used later in order to prepare the
NameError: name 'TEST_IMAGE_PATHS' is not defined
tensorflow google-colaboratory object-detection-api
add a comment |
I tried running tensorflow object detection API on Colab according to here.
However, such an error occurred How can I solve it?
I tried step1.2.3.4.
They maybe run.
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
# Definite input and output Tensors for detection_graph
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.
detection_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.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
for image_path in TEST_IMAGE_PATHS:
image = Image.open(image_path)
# the array based representation of the image will be used later in order to prepare the
# result image with boxes and labels on it.
image_np = load_image_into_numpy_array(image)
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
# Actual detection.
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_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)
plt.figure(figsize=IMAGE_SIZE)
plt.imshow(image_np)
The error I receive is:
NameError
Traceback (most recent call last)
<ipython-input-24-7493eea60222> in <module>()
10 detection_classes =
detection_graph.get_tensor_by_name('detection_classes:0')
11 num_detections =
detection_graph.get_tensor_by_name('num_detections:0')
---> 12 for image_path in TEST_IMAGE_PATHS:
13 image = Image.open(image_path)
14 # the array based representation of the image will be used later in order to prepare the
NameError: name 'TEST_IMAGE_PATHS' is not defined
tensorflow google-colaboratory object-detection-api
Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
The NameError is being raised forTEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.
– Ami F
Dec 21 '18 at 21:25
add a comment |
I tried running tensorflow object detection API on Colab according to here.
However, such an error occurred How can I solve it?
I tried step1.2.3.4.
They maybe run.
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
# Definite input and output Tensors for detection_graph
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.
detection_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.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
for image_path in TEST_IMAGE_PATHS:
image = Image.open(image_path)
# the array based representation of the image will be used later in order to prepare the
# result image with boxes and labels on it.
image_np = load_image_into_numpy_array(image)
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
# Actual detection.
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_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)
plt.figure(figsize=IMAGE_SIZE)
plt.imshow(image_np)
The error I receive is:
NameError
Traceback (most recent call last)
<ipython-input-24-7493eea60222> in <module>()
10 detection_classes =
detection_graph.get_tensor_by_name('detection_classes:0')
11 num_detections =
detection_graph.get_tensor_by_name('num_detections:0')
---> 12 for image_path in TEST_IMAGE_PATHS:
13 image = Image.open(image_path)
14 # the array based representation of the image will be used later in order to prepare the
NameError: name 'TEST_IMAGE_PATHS' is not defined
tensorflow google-colaboratory object-detection-api
I tried running tensorflow object detection API on Colab according to here.
However, such an error occurred How can I solve it?
I tried step1.2.3.4.
They maybe run.
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
# Definite input and output Tensors for detection_graph
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.
detection_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.
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
for image_path in TEST_IMAGE_PATHS:
image = Image.open(image_path)
# the array based representation of the image will be used later in order to prepare the
# result image with boxes and labels on it.
image_np = load_image_into_numpy_array(image)
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
# Actual detection.
(boxes, scores, classes, num) = sess.run(
[detection_boxes, detection_scores, detection_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)
plt.figure(figsize=IMAGE_SIZE)
plt.imshow(image_np)
The error I receive is:
NameError
Traceback (most recent call last)
<ipython-input-24-7493eea60222> in <module>()
10 detection_classes =
detection_graph.get_tensor_by_name('detection_classes:0')
11 num_detections =
detection_graph.get_tensor_by_name('num_detections:0')
---> 12 for image_path in TEST_IMAGE_PATHS:
13 image = Image.open(image_path)
14 # the array based representation of the image will be used later in order to prepare the
NameError: name 'TEST_IMAGE_PATHS' is not defined
tensorflow google-colaboratory object-detection-api
tensorflow google-colaboratory object-detection-api
edited Dec 20 '18 at 7:18
Ankur Aggarwal
1,64922631
1,64922631
asked Dec 20 '18 at 4:54
R typeR type
14
14
Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
The NameError is being raised forTEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.
– Ami F
Dec 21 '18 at 21:25
add a comment |
Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
The NameError is being raised forTEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.
– Ami F
Dec 21 '18 at 21:25
Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
The NameError is being raised for
TEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.– Ami F
Dec 21 '18 at 21:25
The NameError is being raised for
TEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.– Ami F
Dec 21 '18 at 21:25
add a comment |
1 Answer
1
active
oldest
votes
On Analysing your code,it shows you are not running it in Colab.
The error occurs just because you are not initialising the path of test images directory.
while the for loop searches for images in path it throws the error.
so please initialise the path like the blow mentioned code.
PATH_TO_TEST_IMAGES_DIR = 'test_images'
TEST_IMAGE_PATHS = [ os.path.join(PATH_TO_TEST_IMAGES_DIR, 'image-.jpg'.format(i)) for i in range(1, 4) ]
Try this..
add a comment |
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1 Answer
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oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
On Analysing your code,it shows you are not running it in Colab.
The error occurs just because you are not initialising the path of test images directory.
while the for loop searches for images in path it throws the error.
so please initialise the path like the blow mentioned code.
PATH_TO_TEST_IMAGES_DIR = 'test_images'
TEST_IMAGE_PATHS = [ os.path.join(PATH_TO_TEST_IMAGES_DIR, 'image-.jpg'.format(i)) for i in range(1, 4) ]
Try this..
add a comment |
On Analysing your code,it shows you are not running it in Colab.
The error occurs just because you are not initialising the path of test images directory.
while the for loop searches for images in path it throws the error.
so please initialise the path like the blow mentioned code.
PATH_TO_TEST_IMAGES_DIR = 'test_images'
TEST_IMAGE_PATHS = [ os.path.join(PATH_TO_TEST_IMAGES_DIR, 'image-.jpg'.format(i)) for i in range(1, 4) ]
Try this..
add a comment |
On Analysing your code,it shows you are not running it in Colab.
The error occurs just because you are not initialising the path of test images directory.
while the for loop searches for images in path it throws the error.
so please initialise the path like the blow mentioned code.
PATH_TO_TEST_IMAGES_DIR = 'test_images'
TEST_IMAGE_PATHS = [ os.path.join(PATH_TO_TEST_IMAGES_DIR, 'image-.jpg'.format(i)) for i in range(1, 4) ]
Try this..
On Analysing your code,it shows you are not running it in Colab.
The error occurs just because you are not initialising the path of test images directory.
while the for loop searches for images in path it throws the error.
so please initialise the path like the blow mentioned code.
PATH_TO_TEST_IMAGES_DIR = 'test_images'
TEST_IMAGE_PATHS = [ os.path.join(PATH_TO_TEST_IMAGES_DIR, 'image-.jpg'.format(i)) for i in range(1, 4) ]
Try this..
answered Mar 7 at 10:58
Tamil Selvan STamil Selvan S
3817
3817
add a comment |
add a comment |
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Please let me know if there is a way to easily perform object detection with google colab.
– R type
Dec 20 '18 at 5:02
The NameError is being raised for
TEST_IMAGE_PATHS
which is defined in Step 4 of the notebook linked from the medium post you linked to. If the notebook doesn't run for you unmodified top-to-bottom you might want to ask on the blog post. If you've modified it and now it doesn't run, sharing your notebook (view-only) publicly and including its URL in your question may help people help you.– Ami F
Dec 21 '18 at 21:25