search

rizkiarm / LipNet

Keras implementation of 'LipNet: End-to-End Sentence-level Lipreading'
MIT License
638 stars 226 forks source link

Value Error while training random_split #73

Closed riya-maan closed 5 years ago

riya-maan commented 5 years ago

Using all available GPUs. Using TensorFlow backend.

Loading dataset list from cache... Found 0 videos for training. Found 0 videos for validation.

WARNING:tensorflow:From /Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1062: calling reduce_prod (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead WARNING:tensorflow:From /Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1044: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead WARNING:tensorflow:From /Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1008: calling reduce_max (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead

Layer (type) Output Shape Param #

the_input (InputLayer) (None, 75, 100, 50, 3) 0

zero1 (ZeroPadding3D) (None, 77, 104, 54, 3) 0

conv1 (Conv3D) (None, 75, 50, 25, 32) 7232

batc1 (BatchNormalization) (None, 75, 50, 25, 32) 128

actv1 (Activation) (None, 75, 50, 25, 32) 0

spatial_dropout3d_1 (Spatial (None, 75, 50, 25, 32) 0

max1 (MaxPooling3D) (None, 75, 25, 12, 32) 0

zero2 (ZeroPadding3D) (None, 77, 29, 16, 32) 0

conv2 (Conv3D) (None, 75, 25, 12, 64) 153664

batc2 (BatchNormalization) (None, 75, 25, 12, 64) 256

actv2 (Activation) (None, 75, 25, 12, 64) 0

spatial_dropout3d_2 (Spatial (None, 75, 25, 12, 64) 0

max2 (MaxPooling3D) (None, 75, 12, 6, 64) 0

zero3 (ZeroPadding3D) (None, 77, 14, 8, 64) 0

conv3 (Conv3D) (None, 75, 12, 6, 96) 165984

batc3 (BatchNormalization) (None, 75, 12, 6, 96) 384

actv3 (Activation) (None, 75, 12, 6, 96) 0

spatial_dropout3d_3 (Spatial (None, 75, 12, 6, 96) 0

max3 (MaxPooling3D) (None, 75, 6, 3, 96) 0

time_distributed_1 (TimeDist (None, 75, 1728) 0

bidirectional_1 (Bidirection (None, 75, 512) 3048960

bidirectional_2 (Bidirection (None, 75, 512) 1181184

dense1 (Dense) (None, 75, 28) 14364

softmax (Activation) (None, 75, 28) 0

Total params: 4,572,156.0 Trainable params: 4,571,772.0 Non-trainable params: 384.0

WARNING:tensorflow:From /Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1123: calling reduce_mean (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead Traceback (most recent call last): File "/Users/riyamaan/Desktop/LipNet/training/random_split/train.py", line 73, in train(run_name, 0, 20, 3, 100, 50, 75, 32, 50) File "/Users/riyamaan/Desktop/LipNet/training/random_split/train.py", line 69, in train pickle_safe=True) File "/Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/legacy/interfaces.py", line 88, in wrapper return func(*args, **kwargs) File "/Users/riyamaan/anaconda3/lib/python3.6/site-packages/keras/engine/training.py", line 1783, in fit_generator raise ValueError('When using a generator for validation data, ' ValueError: When using a generator for validation data, you must specify a value for validation_steps.

Has anyone had this issue?

Is there a problem with symbolic links? Shall they point to directory containing extracted mouth crop images or to the videos?

riya-maan commented 5 years ago

Resolved!

gzz666 commented 5 years ago

Hey, I have same problem . how do you resolved?

riya-maan commented 5 years ago

Symbolic links were not pointing to the right folder.

gzz666 commented 5 years ago

thanks，resolved.but I meet a problem ,ValueError: output of generator should be a tuple (x, y, sample_weight) or (x, y). Found: None. Do you meet the same issue?can you resolved?