You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
into tensorflow format that already worked on the model that was linked in the video (for checking purposes and it worked 😄) however I tried to take the same approach to a custom trained model that detects "mice" (for test analysis purposes) and I get this error:
in load_darknet_weights
conv_shape).transpose([2, 3, 1, 0])
ValueError: cannot reshape array of size 4607 into shape (18,256,1,1)
so is there a way to solve this issue?
So then I added these lines in utils.py:
conv_shape = (math.floor(filters), math.floor(in_dim), size, size)
conv_weights = np.fromfile(wf, dtype=np.float32, count=np.product(conv_shape))
if conv_weights.shape[0]<filters*in_dim:
conv_weights = np.append(conv_weights,[0])
and it worked but when it came time to run object_tracker.py (yes a file from another repo but has the same convert.py and utils.py) I had this error:
tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found.
(0) Invalid argument: Input to reshape is a tensor with 3042 values, but the requested shape requires a multiple of 43095
[[{{node yolo_output_0/lambda/Reshape}}]]
[[yolo_nms/Reshape_9/_1477]]
(1) Invalid argument: Input to reshape is a tensor with 3042 values, but the requested shape requires a multiple of 43095
[[{{node yolo_output_0/lambda/Reshape}}]]
The text was updated successfully, but these errors were encountered:
Hatem-Jr
changed the title
Converting a custom yolov3 dataset
Converting a custom yolov3 model
Jul 21, 2021
I am trying to convert this yolov3 custom model: https://drive.google.com/drive/folders/17jysPykGMkNw66lDMd0kryybCvGOesKi?usp=sharing
with this .cfg file: https://github.com/heltonmaia/ECT-proj-cnn-mice/blob/master/cfg/yolov3.cfg
into tensorflow format that already worked on the model that was linked in the video (for checking purposes and it worked 😄) however I tried to take the same approach to a custom trained model that detects "mice" (for test analysis purposes) and I get this error:
in load_darknet_weights
conv_shape).transpose([2, 3, 1, 0])
ValueError: cannot reshape array of size 4607 into shape (18,256,1,1)
so is there a way to solve this issue?
So then I added these lines in utils.py:
conv_shape = (math.floor(filters), math.floor(in_dim), size, size)
conv_weights = np.fromfile(wf, dtype=np.float32, count=np.product(conv_shape))
if conv_weights.shape[0]<filters*in_dim:
conv_weights = np.append(conv_weights,[0])
before: conv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0])
and it worked but when it came time to run object_tracker.py (yes a file from another repo but has the same convert.py and utils.py) I had this error:
tensorflow.python.framework.errors_impl.InvalidArgumentError: 2 root error(s) found.
(0) Invalid argument: Input to reshape is a tensor with 3042 values, but the requested shape requires a multiple of 43095
[[{{node yolo_output_0/lambda/Reshape}}]]
[[yolo_nms/Reshape_9/_1477]]
(1) Invalid argument: Input to reshape is a tensor with 3042 values, but the requested shape requires a multiple of 43095
[[{{node yolo_output_0/lambda/Reshape}}]]
The text was updated successfully, but these errors were encountered: