Models: ValueError: assignment destination is read-only

[T-chuangxin]

mac os 14

I have no idea about this !!!

Here is the code , i have...
`def detect_objects(image_np, sess, detection_graph):
# 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)
return image_np

def process_image(image):
# NOTE: The output you return should be a color image (3 channel) for processing video below
# you should return the final output (image with lines are drawn on lanes)
with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
image_process = detect_objects(image, sess, detection_graph)
return image_process

white_output = '/Users/tianchuangxin1/models/research/object_detection/video3_3_out.mp4'
clip1 = VideoFileClip("/Users/tianchuangxin1/models/research/object_detection/video1.mp4").subclip(0,1)
white_clip = clip1.fl_image(process_image) #NOTE: this function expects color images!!s
%time white_clip.write_videofile(white_output, audio=False)

`

The issue

`ValueError Traceback (most recent call last)
in ()
1 white_output = '/Users/tianchuangxin1/models/research/object_detection/video3_3_out.mp4'
2 clip1 = VideoFileClip("/Users/tianchuangxin1/models/research/object_detection/video1.mp4").subclip(0,1)
----> 3 white_clip = clip1.fl_image(process_image) #NOTE: this function expects color images!!s
4 get_ipython().magic('time white_clip.write_videofile(white_output, audio=False)')

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/video/VideoClip.py in fl_image(self, image_func, apply_to)
509 if apply_to is None:
510 apply_to = []
--> 511 return self.fl(lambda gf, t: image_func(gf(t)), apply_to)
512
513 # --------------------------------------------------------------

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/Clip.py in fl(self, fun, apply_to, keep_duration)
136
137 #mf = copy(self.make_frame)
--> 138 newclip = self.set_make_frame(lambda t: fun(self.get_frame, t))
139
140 if not keep_duration:

in set_make_frame(self, mf)

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/decorators.py in outplace(f, clip, a, *k)
12 """ Applies f(clip.copy(), a, *k) and returns clip.copy()"""
13 newclip = clip.copy()
---> 14 f(newclip, a, *k)
15 return newclip
16

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/video/VideoClip.py in set_make_frame(self, mf)
664 """
665 self.make_frame = mf
--> 666 self.size = self.get_frame(0).shape[:2][::-1]
667
668 @outplace

in get_frame(self, t)

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/decorators.py in wrapper(f, a, *kw)
87 new_kw = {k: fun(v) if k in varnames else v
88 for (k,v) in kw.items()}
---> 89 return f(new_a, *new_kw)
90 return decorator.decorator(wrapper)
91

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/Clip.py in get_frame(self, t)
93 return frame
94 else:
---> 95 return self.make_frame(t)
96
97 def fl(self, fun, apply_to=None, keep_duration=True):

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/Clip.py in (t)
136
137 #mf = copy(self.make_frame)
--> 138 newclip = self.set_make_frame(lambda t: fun(self.get_frame, t))
139
140 if not keep_duration:

/Users/tianchuangxin1/anaconda/lib/python3.5/site-packages/moviepy/video/VideoClip.py in (gf, t)
509 if apply_to is None:
510 apply_to = []
--> 511 return self.fl(lambda gf, t: image_func(gf(t)), apply_to)
512
513 # --------------------------------------------------------------

in process_image(image)
4 with detection_graph.as_default():
5 with tf.Session(graph=detection_graph) as sess:
----> 6 image_process = detect_objects(image, sess, detection_graph)
7 return image_process

in detect_objects(image_np, sess, detection_graph)
26 category_index,
27 use_normalized_coordinates=True,
---> 28 line_thickness=8)
29 return image_np

/Users/tianchuangxin1/models/research/object_detection/utils/visualization_utils.py in visualize_boxes_and_labels_on_image_array(image, boxes, classes, scores, category_index, instance_masks, instance_boundaries, keypoints, use_normalized_coordinates, max_boxes_to_draw, min_score_thresh, agnostic_mode, line_thickness, groundtruth_box_visualization_color, skip_scores, skip_labels)
664 thickness=line_thickness,
665 display_str_list=box_to_display_str_map[box],
--> 666 use_normalized_coordinates=use_normalized_coordinates)
667 if keypoints is not None:
668 draw_keypoints_on_image_array(

/Users/tianchuangxin1/models/research/object_detection/utils/visualization_utils.py in draw_bounding_box_on_image_array(image, ymin, xmin, ymax, xmax, color, thickness, display_str_list, use_normalized_coordinates)
128 thickness, display_str_list,
129 use_normalized_coordinates)
--> 130 np.copyto(image, np.array(image_pil))
131
132

ValueError: assignment destination is read-only

`

[bensdm]

this is due to numpy version <1.16, you can fix it by adding before line 130: image.setflags(write=1)
or updating numpy !

[tensorflowbutler]

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
What is the top-level directory of the model you are using
Have I written custom code
OS Platform and Distribution
TensorFlow installed from
TensorFlow version
Bazel version
CUDA/cuDNN version
GPU model and memory
Exact command to reproduce

[rn-lpz]

It happens the same to me. I had version 1.15 of numpy. I have installed version 1.16.2 and the error does not disappear. Also try adding the line of code but it does not work.

this is due to numpy version <1.16, you can fix it by adding before line 130: image.setflags(write=1)
or updating numpy !

[amm385]

i had a similar issue, solved it in a hacky way by simply creating a copy of the image array, e.g.

image_copy = np.copy(image_np)
vis_util.visualize_boxes_and_labels_on_image_array(
    image_copy,
    np.squeeze(boxes),
    np.squeeze(classes).astype(np.int32),
    np.squeeze(scores),
    category_index,
    use_normalized_coordinates=True,
    line_thickness=8)
return image_copy

[msaqib17]

One can use np.array(image) to avoid this error

vis_util.visualize_boxes_and_labels_on_image_array(
np.array(image),
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8)