Hello!
I have encounter an error during training GluonCV Faster RCNN model.
I was trying to build a Faster RCNN model to detect bacteria in the image.
However, the number of bacteria in a single image that is labeled is super huge!!(>1000 BBox/image)
I’ve encounter an error during training that stop the training procedure in the beginning. I tried to reduce the label number in every single image and everything goes well again. Because of that, I was thinking about if this error is generate from having too many objects within a single image?
I’d like to know
**1. Is there any limitation related to the maximum object during training period? **
2. Is it possible this can be solve or bypass?
3. What’s the 2300 vs. 3146 number coming from?
Thank you in advance!
Model: Faster RCNN
Backbone: resnet50_v1b
Input image size: 1024x1024
**MXNetError: [12:23:54] src/operator/tensor/./matrix_op-inl.h:1442: Check failed: ishape[i] >= from_shape[i] (2300 vs. 3146) : Slice axis 0 with size 3146exceeds limit of input with size 2300**
Complete error message
net_name: **faster_rcnn_resnet50_v1b_bact** will be used.
loading annotations into memory...
Done (t=0.04s)
creating index...
index created!
loading annotations into memory...
Done (t=0.46s)
creating index...
index created!
batch_size 1
/usr/local/lib/python3.6/dist-packages/mxnet/gluon/parameter.py:703: UserWarning: Constant parameter "normalizedperclassboxcenterencoder4_means" does not support grad_req other than "null", and new value "write" is ignored.
'is ignored.'.format(self.name, req))
/usr/local/lib/python3.6/dist-packages/mxnet/gluon/parameter.py:703: UserWarning: Constant parameter "normalizedperclassboxcenterencoder4_stds" does not support grad_req other than "null", and new value "write" is ignored.
'is ignored.'.format(self.name, req))
/usr/local/lib/python3.6/dist-packages/mxnet/gluon/parameter.py:703: UserWarning: Constant parameter "fasterrcnn1_rpn0_rpnanchorgenerator0_anchor_" does not support grad_req other than "null", and new value "write" is ignored.
'is ignored.'.format(self.name, req))
INFO:root:<__main__.Args object at 0x7f157cc04358>
INFO:root:Start training from [Epoch 0]
---------------------------------------------------------------------------
MXNetError Traceback (most recent call last)
<ipython-input-51-0bba58febb4a> in <module>()
198
199 # training
--> 200 train(net, train_data, val_data, eval_metric, batch_size, ctx, args)
11 frames
/usr/local/lib/python3.6/dist-packages/mxnet/base.py in check_call(ret)
253 """
254 if ret != 0:
--> 255 raise MXNetError(py_str(_LIB.MXGetLastError()))
256
257
**MXNetError: [12:23:54] src/operator/tensor/./matrix_op-inl.h:1442: Check failed: ishape[i] >= from_shape[i] (2300 vs. 3146) : Slice axis 0 with size 3146exceeds limit of input with size 2300**