Hi All,
I followed the tutorial about retraining model, downloaded the dashcamnet model, prepared my tfrecords, and started the tlt-train command. But I got error saying “ValueError: Cannot reshape a tensor with 119808 elements to shape”
I intend to retrain the model to detect “holes” on the road without losing the ability of detecting cars, people, and roadsigns at the same time.
The log is as below:
Blockquote
“/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py”, line 1662, in _create_c_op
raise ValueError(str(e))
ValueError: Cannot reshape a tensor with 119808 elements to shape [4,7,4,34,60] (228480 elements) for ‘reshape_1_1/Reshape’ (op: ‘Reshape’) with input shapes: [4,16,24,78], [5] and with input tensors computed as partial shapes: input[1] = [4,7,4,34,60].
Blockquote
Looks like it is a tensorflow related problem, but where to figure and fix it?
Thanks,
Could you please share your training spec?
BTW in the spec, I added several classes which are D00, D10… which stand for different types of holes on road.
In the spec, I did nothing regarding the original detectable objects types that are “cars”,“people”,“roadsigns” and “two-wheelers” cause I think I only intend to add the ability of detecting the “holes”, all my spec should be new detection class related. (which I don’t know if correct or not). If I am wrong, what should I do to include the old classes
thanks,
My dataset’s images are all jpg format, and 600*600 pixels.
In the spec, I specified
"augmentation_config {
preprocessing {
output_image_width: 600
output_image_height: 600
…
"
I cannot find other places where I can set the training images size be 600*600.
What should I do with the training images?
Thanks
Please resize images and labels to “W, H are multiples of 16”.
Or you can set
output_image_width: 608
output_image_height: 608
and remove “load_graph: true”