danielvarga / keras-finetuning Goto Github PK

Hi Daniel.

Thanks for uploading the post, I have learned a lot from studying the code but I am having trouble running webcam.py. When I try to run it I get this error ValueError: You are trying to load a weight file containing 190 layers into a model with 2 layers.

Can you give me some guidance on how to fix it please?

Hi,
when I run train.py on some test data I get the following error.
Any advise ?

Traceback (most recent call last):
  File "train.py", line 34, in <module>
    X, y, tags = dataset.dataset(data_directory, n)
  File "dataset.py", line 47, in dataset
    assert chan == 3

AssertionError

Throws the following error as soon as the images are loaded:

Contents of keras.json:
{
"image_dim_ordering": "th",
"epsilon": 1e-07,
"floatx": "float32",
"backend": "tensorflow"
}

P.S. : Even tried replacing 'th' with 'tf', but I guess the part causing this error comes before any difference between 'th' and 'tf' can appear.

ValueError: NumpyArrayIterator is set to use the data format convention "channels_last" (channels on axis 3), i.e. expected either 1, 3 or 4 channels on axis 3. However, it was passed an array with shape (80, 3, 224, 224) (224 channels).

I can load dataset and model successfully, but I can't find the answer online. I run the code in windows7, and I modify the code, so I don't know the reason. Is this a problem with data processing?

Hitting an error here when i run the script, going to have a look around now i think there is something wrong with pillow in my environment though i have tried to create a fresh env and im still hitting the same error!

Using TensorFlow backend. loading dataset Traceback (most recent call last): File "train.py", line 34, in <module> X, y, tags = dataset.dataset(data_directory, n) File "/Users/roryw10/keras-finetuning/dataset.py", line 45, in dataset img = scipy.misc.imread(filename) File "//anaconda/envs/finetune/lib/python2.7/site-packages/scipy/misc/pilutil.py", line 154, in imread im = Image.open(name) File "//anaconda/envs/finetune/lib/python2.7/site-packages/PIL/Image.py", line 1980, in open raise IOError("cannot identify image file") IOError: cannot identify image file

I got this error while running train.py file, I use Theano backend.

training the newly added dense layers
Epoch 1/20
Traceback (most recent call last):
File "train.py", line 134, in

File "/Users/justinushermawan/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 1475, in fit_generator
class_weight=class_weight)
File "/Users/justinushermawan/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 1244, in train_on_batch
check_batch_dim=True)
File "/Users/justinushermawan/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 1000, in _standardize_user_data
check_loss_and_target_compatibility(y, self.loss_functions, self.internal_output_shapes)
File "/Users/justinushermawan/tensorflow/lib/python2.7/site-packages/keras/engine/training.py", line 196, in check_loss_and_target_compatibility
' while using as loss categorical_crossentropy. '
Exception: You are passing a target array of shape (3, 1) while using as loss categorical_crossentropy. categorical_crossentropy expects targets to be binary matrices (1s and 0s) of shape (samples, classes). If your targets are integer classes, you can convert them to the expected format via:

from keras.utils.np_utils import to_categorical
y_binary = to_categorical(y_int)

Alternatively, you can use the loss function sparse_categorical_crossentropy instead, which does expect integer targets.

When using the theano backend for running this code, the fine-tuning of the top layer runs perfectly fine. However, as soon as the tweaking of the penultimate layer starts, the following error is thrown:

I've tried running the code thrice on different data-sets (to make sure that it isn't a problem with corrupt,invalid data,etc.)