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moabitcoin / holy-edge

Holistically-Nested Edge Detection
https://arxiv.org/pdf/1504.06375.pdf
GNU General Public License v3.0
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Dimension Mismatch #16

Open moinnadeem opened 6 years ago

moinnadeem commented 6 years ago

Console Error Log

2018-05-06 17:38:44.599331: W tensorflow/core/framework/op_kernel.cc:1152] Invalid argument: ConcatOp : Dimensions of inputs should match: shape[0] = [1,400,600,1] vs. shape[4] = [1,400,608,1] [[Node: concat = ConcatV2[N=5, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](side_1/conv2d_transpose, side_2/conv2d_transpose, side_3/conv2d_transpose, side_4/conv2d_transpose, side_5/conv2d_transpose, concat/axis)]] Traceback (most recent call last): File "run-hed.py", line 64, in main(args) File "run-hed.py", line 44, in main tester.run(session) File "/home/mnadeem/research/holy-edge/hed/test.py", line 68, in run edgemap = session.run(self.model.predictions, feed_dict={self.model.images: [im]}) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 778, in run run_metadata_ptr) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 982, in _run feed_dict_string, options, run_metadata) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1032, in _do_run target_list, options, run_metadata) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1052, in _do_call raise type(e)(node_def, op, message) tensorflow.python.framework.errors_impl.InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape[0] = [1,400,600,1] vs. shape[4] = [1,400,608,1] [[Node: concat = ConcatV2[N=5, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](side_1/conv2d_transpose, side_2/conv2d_transpose, side_3/conv2d_transpose, side_4/conv2d_transpose, side_5/conv2d_transpose, concat/axis)]]

Caused by op u'concat', defined at: File "run-hed.py", line 64, in main(args) File "run-hed.py", line 43, in main tester.setup(session) File "/home/mnadeem/research/holy-edge/hed/test.py", line 37, in setup self.model = Vgg16(self.cfgs, run='testing') File "/home/mnadeem/research/holy-edge/hed/models/vgg16.py", line 30, in init self.define_model() File "/home/mnadeem/research/holy-edge/hed/models/vgg16.py", line 81, in define_model self.fuse = self.conv_layer(tf.concat(self.side_outputs, axis=3), File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1034, in concat name=name) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 519, in _concat_v2 name=name) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op op_def=op_def) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op original_op=self._default_original_op, op_def=op_def) File "/home/mnadeem/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in init self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): ConcatOp : Dimensions of inputs should match: shape[0] = [1,400,600,1] vs. shape[4] = [1,400,608,1] [[Node: concat = ConcatV2[N=5, T=DT_FLOAT, Tidx=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](side_1/conv2d_transpose, side_2/conv2d_transpose, side_3/conv2d_transpose, side_4/conv2d_transpose, side_5/conv2d_transpose, concat/axis)]]

Config:

training: dir: HED-BSDS list: HED-BSDS/train_pair.lst # image_width: 480 image_height: 480 n_channels: 3

testing data

testing: dir: mrl_database list: mrl_database/files.lst # image_width: 600 image_height: 400 n_channels: 3

I just want to use the pre-trained weights.

yfnn commented 6 years ago

I have similar question. Have you solved it?

chetanreddym commented 6 years ago

@moinnadeem @yfnn @sandhawalia Has anybody solved this problem?