Error using image dataset of 640x360 for training using SqueezeDet.

[muthiyanbhushan]

Hello,

I changed the image size in src/config/kitty_squeezeDet_config.py file from to 640x360 for 96 classes and also added class names in the config.py file, keeping all other parameters same. I get error as:

Cannot find fire10/squeeze1x1 in the pretrained model. Use randomly initialized parameters Cannot find fire10/expand1x1 in the pretrained model. Use randomly initialized parameters Cannot find fire10/expand3x3 in the pretrained model. Use randomly initialized parameters Cannot find fire11/squeeze1x1 in the pretrained model. Use randomly initialized parameters Cannot find fire11/expand1x1 in the pretrained model. Use randomly initialized parameters Cannot find fire11/expand3x3 in the pretrained model. Use randomly initialized parameters Cannot find conv12 in the pretrained model. Use randomly initialized parameters Traceback (most recent call last): File "./src/train.py", line 359, in tf.app.run() File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/platform/app.py", line 124, in run _sys.exit(main(argv)) File "./src/train.py", line 355, in main train() File "./src/train.py", line 128, in train model = SqueezeDet(mc) File "/home/bhushan/squeezeDet/src/nets/squeezeDet.py", line 25, in init self._add_interpretation_graph() File "/home/bhushan/squeezeDet/src/nn_skeleton.py", line 159, in _add_interpretation_graph name='pred_class_probs' File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3997, in reshape "Reshape", tensor=tensor, shape=shape, name=name) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper op_def=op_def) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3162, in create_op compute_device=compute_device) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 3208, in _create_op_helper set_shapes_for_outputs(op) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2427, in set_shapes_for_outputs return _set_shapes_for_outputs(op) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2400, in _set_shapes_for_outputs shapes = shape_func(op) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2330, in call_with_requiring return call_cpp_shape_fn(op, require_shape_fn=True) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 627, in call_cpp_shape_fn require_shape_fn) File "/home/bhushan/anaconda3/envs/squeezedet/lib/python2.7/site-packages/tensorflow/python/framework/common_shapes.py", line 691, in _call_cpp_shape_fn_impl raise ValueError(err.message) ValueError: Cannot reshape a tensor with 207360 elements to shape [4,16848,96] (6469632 elements) for 'interpret_output/pred_class_probs' (op: 'Reshape') with input shapes: [2160,96], [3] and with input tensors computed as partial shapes: input[1] = [4,16848,96].

Do I need to change any more parameters?

Thanks.

[amanmeetgarg]

you need to ensure that the dimensions / grid_indices = 16 .. if this ratio is violated, this error above occurs.. check the authors original code and you would find that the ImgHeight/Anchor_grid_height = 16

[muthiyanbhushan]

Hello @amanmeetgarg,

In which file will I get this information? Thanks.

[amanmeetgarg]

squeezeDet/src/config/kitti_squeezeDet_config.py

[muthiyanbhushan]

@amanmeetgarg Thanks. I was able to train it.

[amanmeetgarg]

Glad was of help. All the best.

[muthiyanbhushan]

Hello @amanmeetgarg,

I am trying to run the model for 100000 steps.

The model checkpoint saved has 3 files.

1. model.ckpt-99999.data-00000-of-00001
2. model.ckpt-99999.index
3. model.ckpt-99999.meta But the final checkpoint value is not being stored like original checkpoint "model.ckpt-87000".

Can you please let me know how can I get this final weights?

Thanks.

[amanmeetgarg]

Read the documentation from tensorflow

another reasonable source https://blog.metaflow.fr/tensorflow-how-to-freeze-a-model-and-serve-it-with-a-python-api-d4f3596b3adc