Keras ImageDataGenerator: problem with data and label shape
I wanted to generate more images using Keras as you can see in here,
using this code (almost the same as source>Random Rotations):
# Random Rotations
from keras.datasets import mnist
from keras.preprocessing.image import ImageDataGenerator
from matplotlib import pyplot
from keras import backend as K
datagen = ImageDataGenerator(rotation_range=90)
# fit parameters from data
datagen.fit(cats["images"])
print(np.asarray(cats["label"]).shape) #output=(12464,)
print(np.asarray(cats["images"]).shape) #output=(12464, 60, 60, 1)
# configure batch size and retrieve one batch of images
for X_batch, y_batch in datagen.flow(cats["images"], cats["label"], batch_size=9):
# create a grid of 3x3 images
for i in range(0, 9):
pyplot.subplot(330 + 1 + i)
pyplot.imshow(X_batch[i].reshape(28, 28), cmap=pyplot.get_cmap('gray'))
# show the plot
pyplot.show()
break
But I get the following error:
ValueError:
x(images tensor) andy(labels) should have the same
length. Found: x.shape = (60, 60, 1), y.shape = (12464,)
This might help for further inspections :
I imagine there should be something wrong with the library as if I change the shape of my image into 60x60 instead of 60x60x1 I'll get:
ValueError: Input to
.fit()should have rank 4. Got array with
shape: (12464, 60, 60)
python tensorflow image-processing keras
edited Jan 2 at 11:45
today
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
add a comment |
I wanted to generate more images using Keras as you can see in here,
using this code (almost the same as source>Random Rotations):
# Random Rotations
from keras.datasets import mnist
from keras.preprocessing.image import ImageDataGenerator
from matplotlib import pyplot
from keras import backend as K
datagen = ImageDataGenerator(rotation_range=90)
# fit parameters from data
datagen.fit(cats["images"])
print(np.asarray(cats["label"]).shape) #output=(12464,)
print(np.asarray(cats["images"]).shape) #output=(12464, 60, 60, 1)
# configure batch size and retrieve one batch of images
for X_batch, y_batch in datagen.flow(cats["images"], cats["label"], batch_size=9):
# create a grid of 3x3 images
for i in range(0, 9):
pyplot.subplot(330 + 1 + i)
pyplot.imshow(X_batch[i].reshape(28, 28), cmap=pyplot.get_cmap('gray'))
# show the plot
pyplot.show()
break
But I get the following error:
ValueError:
x(images tensor) andy(labels) should have the same
length. Found: x.shape = (60, 60, 1), y.shape = (12464,)
This might help for further inspections :
I imagine there should be something wrong with the library as if I change the shape of my image into 60x60 instead of 60x60x1 I'll get:
ValueError: Input to
.fit()should have rank 4. Got array with
shape: (12464, 60, 60)
python tensorflow image-processing keras
edited Jan 2 at 11:45
today
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
add a comment |
I wanted to generate more images using Keras as you can see in here,
using this code (almost the same as source>Random Rotations):
# Random Rotations
from keras.datasets import mnist
from keras.preprocessing.image import ImageDataGenerator
from matplotlib import pyplot
from keras import backend as K
datagen = ImageDataGenerator(rotation_range=90)
# fit parameters from data
datagen.fit(cats["images"])
print(np.asarray(cats["label"]).shape) #output=(12464,)
print(np.asarray(cats["images"]).shape) #output=(12464, 60, 60, 1)
# configure batch size and retrieve one batch of images
for X_batch, y_batch in datagen.flow(cats["images"], cats["label"], batch_size=9):
# create a grid of 3x3 images
for i in range(0, 9):
pyplot.subplot(330 + 1 + i)
pyplot.imshow(X_batch[i].reshape(28, 28), cmap=pyplot.get_cmap('gray'))
# show the plot
pyplot.show()
break
But I get the following error:
ValueError:
x(images tensor) andy(labels) should have the same
length. Found: x.shape = (60, 60, 1), y.shape = (12464,)
This might help for further inspections :
I imagine there should be something wrong with the library as if I change the shape of my image into 60x60 instead of 60x60x1 I'll get:
ValueError: Input to
.fit()should have rank 4. Got array with
shape: (12464, 60, 60)
python tensorflow image-processing keras
edited Jan 2 at 11:45
today
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
I wanted to generate more images using Keras as you can see in here,
using this code (almost the same as source>Random Rotations):
# Random Rotations
from keras.datasets import mnist
from keras.preprocessing.image import ImageDataGenerator
from matplotlib import pyplot
from keras import backend as K
datagen = ImageDataGenerator(rotation_range=90)
# fit parameters from data
datagen.fit(cats["images"])
print(np.asarray(cats["label"]).shape) #output=(12464,)
print(np.asarray(cats["images"]).shape) #output=(12464, 60, 60, 1)
# configure batch size and retrieve one batch of images
for X_batch, y_batch in datagen.flow(cats["images"], cats["label"], batch_size=9):
# create a grid of 3x3 images
for i in range(0, 9):
pyplot.subplot(330 + 1 + i)
pyplot.imshow(X_batch[i].reshape(28, 28), cmap=pyplot.get_cmap('gray'))
# show the plot
pyplot.show()
break
But I get the following error:
ValueError:
x(images tensor) andy(labels) should have the same
length. Found: x.shape = (60, 60, 1), y.shape = (12464,)
This might help for further inspections :
I imagine there should be something wrong with the library as if I change the shape of my image into 60x60 instead of 60x60x1 I'll get:
ValueError: Input to
.fit()should have rank 4. Got array with
shape: (12464, 60, 60)
python tensorflow image-processing keras
python tensorflow image-processing keras
edited Jan 2 at 11:45
today
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
edited Jan 2 at 11:45
today
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
edited Jan 2 at 11:45
today
11.1k22038
edited Jan 2 at 11:45
today
11.1k22038
edited Jan 2 at 11:45
today
11.1k22038
11.1k22038
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
asked Jan 2 at 11:22
Mahdi RafatjahMahdi Rafatjah
555317
555317
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
It is very likely that the cats['images'] and cats['labels'] are Python lists. First convert them to arrays using np.array and then pass them to flow method:
cats['images'] = np.array(cats['images'])
cats['labels'] = np.array(cats['labels'])
answered Jan 2 at 11:42
todaytoday
11.1k22038
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
add a comment |
You need to change the shape of your labels
labels = np.asarray(cats["label"]).reshape(( -1 , 1 ))
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
This does not work and produces almost identical error "ValueError:x(images tensor) andy(labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"
– Mahdi Rafatjah
Jan 2 at 15:26
add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
It is very likely that the cats['images'] and cats['labels'] are Python lists. First convert them to arrays using np.array and then pass them to flow method:
cats['images'] = np.array(cats['images'])
cats['labels'] = np.array(cats['labels'])
answered Jan 2 at 11:42
todaytoday
11.1k22038
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
add a comment |
It is very likely that the cats['images'] and cats['labels'] are Python lists. First convert them to arrays using np.array and then pass them to flow method:
cats['images'] = np.array(cats['images'])
cats['labels'] = np.array(cats['labels'])
answered Jan 2 at 11:42
todaytoday
11.1k22038
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
add a comment |
It is very likely that the cats['images'] and cats['labels'] are Python lists. First convert them to arrays using np.array and then pass them to flow method:
cats['images'] = np.array(cats['images'])
cats['labels'] = np.array(cats['labels'])
answered Jan 2 at 11:42
todaytoday
11.1k22038
It is very likely that the cats['images'] and cats['labels'] are Python lists. First convert them to arrays using np.array and then pass them to flow method:
cats['images'] = np.array(cats['images'])
cats['labels'] = np.array(cats['labels'])
answered Jan 2 at 11:42
todaytoday
11.1k22038
answered Jan 2 at 11:42
todaytoday
11.1k22038
answered Jan 2 at 11:42
todaytoday
11.1k22038
answered Jan 2 at 11:42
todaytoday
11.1k22038
11.1k22038
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
add a comment |
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
I expected the following error for this situation "AttributeError: 'list' object has no attribute 'shape'" That is why I never think of that. So much thanks by the way.
– Mahdi Rafatjah
Jan 2 at 15:24
add a comment |
You need to change the shape of your labels
labels = np.asarray(cats["label"]).reshape(( -1 , 1 ))
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
This does not work and produces almost identical error "ValueError:x(images tensor) andy(labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"
– Mahdi Rafatjah
Jan 2 at 15:26
add a comment |
You need to change the shape of your labels
labels = np.asarray(cats["label"]).reshape(( -1 , 1 ))
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
This does not work and produces almost identical error "ValueError:x(images tensor) andy(labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"
– Mahdi Rafatjah
Jan 2 at 15:26
add a comment |
You need to change the shape of your labels
labels = np.asarray(cats["label"]).reshape(( -1 , 1 ))
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
You need to change the shape of your labels
labels = np.asarray(cats["label"]).reshape(( -1 , 1 ))
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
answered Jan 2 at 11:40
Shubham PanchalShubham Panchal
534210
534210
This does not work and produces almost identical error "ValueError:x(images tensor) andy(labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"
– Mahdi Rafatjah
Jan 2 at 15:26
add a comment |
This does not work and produces almost identical error "ValueError:x(images tensor) andy(labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"
– Mahdi Rafatjah
Jan 2 at 15:26
This does not work and produces almost identical error "ValueError:
x (images tensor) and y (labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"– Mahdi Rafatjah
Jan 2 at 15:26
This does not work and produces almost identical error "ValueError:
x (images tensor) and y (labels) should have the same length. Found: x.shape = (60, 60, 1), y.shape = (12464, 1)"– Mahdi Rafatjah
Jan 2 at 15:26
add a comment |
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