Keras flow_from_directory() read only from selected sub-directoriesHow to manually specify class labels in keras flow_from_directory?Keras ImageDataGenerator method flow_from_directoryKeras flow_from_directory class indexkeras ImageDataGenerator flow_from_directory generated dataSplit data directory into training and test directory with sub directory structure preservedDoes Keras flow_from_directory iterate through every sample in a directory?How to access images directly from Google Cloud Storage (GCS) when using Keras?Low validation accuracy with good training accuracy - keras imagedatagenerator flow_from_directory categorical classificationHow to load images for classification problem using KerasFolder structure Keras ImageDataGenerator
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Keras flow_from_directory() read only from selected sub-directories
How to manually specify class labels in keras flow_from_directory?Keras ImageDataGenerator method flow_from_directoryKeras flow_from_directory class indexkeras ImageDataGenerator flow_from_directory generated dataSplit data directory into training and test directory with sub directory structure preservedDoes Keras flow_from_directory iterate through every sample in a directory?How to access images directly from Google Cloud Storage (GCS) when using Keras?Low validation accuracy with good training accuracy - keras imagedatagenerator flow_from_directory categorical classificationHow to load images for classification problem using KerasFolder structure Keras ImageDataGenerator
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty height:90px;width:728px;box-sizing:border-box;
I have a directory structure as follows.
train
|- dog --> contains image files of dogs
|- cat --> contains image files of cats
|- elephant --> contains image files of elephants
I want to train a CNN to identify animals, but only for cats and dogs and not elephants.
I want to use keras ImageDataGenerator class to augment data and flow_from_directory() method to read the image files.
train_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True)
The above code will read data from all sub-directories of 'train', which I don't want. One option is to create a new directory and copy of 'dog' and 'cat' sub-directories along with the files inside it. But is there a way to control it from flow_from_directory() method itself?
tensorflow keras deep-learning conv-neural-network
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
add a comment |
I have a directory structure as follows.
train
|- dog --> contains image files of dogs
|- cat --> contains image files of cats
|- elephant --> contains image files of elephants
I want to train a CNN to identify animals, but only for cats and dogs and not elephants.
I want to use keras ImageDataGenerator class to augment data and flow_from_directory() method to read the image files.
train_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True)
The above code will read data from all sub-directories of 'train', which I don't want. One option is to create a new directory and copy of 'dog' and 'cat' sub-directories along with the files inside it. But is there a way to control it from flow_from_directory() method itself?
tensorflow keras deep-learning conv-neural-network
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
add a comment |
I have a directory structure as follows.
train
|- dog --> contains image files of dogs
|- cat --> contains image files of cats
|- elephant --> contains image files of elephants
I want to train a CNN to identify animals, but only for cats and dogs and not elephants.
I want to use keras ImageDataGenerator class to augment data and flow_from_directory() method to read the image files.
train_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True)
The above code will read data from all sub-directories of 'train', which I don't want. One option is to create a new directory and copy of 'dog' and 'cat' sub-directories along with the files inside it. But is there a way to control it from flow_from_directory() method itself?
tensorflow keras deep-learning conv-neural-network
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
I have a directory structure as follows.
train
|- dog --> contains image files of dogs
|- cat --> contains image files of cats
|- elephant --> contains image files of elephants
I want to train a CNN to identify animals, but only for cats and dogs and not elephants.
I want to use keras ImageDataGenerator class to augment data and flow_from_directory() method to read the image files.
train_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True)
The above code will read data from all sub-directories of 'train', which I don't want. One option is to create a new directory and copy of 'dog' and 'cat' sub-directories along with the files inside it. But is there a way to control it from flow_from_directory() method itself?
tensorflow keras deep-learning conv-neural-network
tensorflow keras deep-learning conv-neural-network
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
asked Mar 24 at 20:40
Supratim HaldarSupratim Haldar
1,255518
1,255518
add a comment |
add a comment |
1 Answer
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oldest
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Assuming that I understood your question in the right way, this should help you:
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True, classes=["dog", "cat"])
This will read only the images from the directories dog and cat, leave out the elephant directory and provide distinct categorical labels for them.
answered Mar 24 at 21:09
gorjangorjan
1,652617
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
active
oldest
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active
oldest
votes
Assuming that I understood your question in the right way, this should help you:
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True, classes=["dog", "cat"])
This will read only the images from the directories dog and cat, leave out the elephant directory and provide distinct categorical labels for them.
answered Mar 24 at 21:09
gorjangorjan
1,652617
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
add a comment |
Assuming that I understood your question in the right way, this should help you:
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True, classes=["dog", "cat"])
This will read only the images from the directories dog and cat, leave out the elephant directory and provide distinct categorical labels for them.
answered Mar 24 at 21:09
gorjangorjan
1,652617
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
add a comment |
Assuming that I understood your question in the right way, this should help you:
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True, classes=["dog", "cat"])
This will read only the images from the directories dog and cat, leave out the elephant directory and provide distinct categorical labels for them.
answered Mar 24 at 21:09
gorjangorjan
1,652617
Assuming that I understood your question in the right way, this should help you:
train_generator = train_datagen.flow_from_directory(directory='train', class_mode='categorical', target_size=(64,64), batch_size=16, shuffle=True, classes=["dog", "cat"])
This will read only the images from the directories dog and cat, leave out the elephant directory and provide distinct categorical labels for them.
answered Mar 24 at 21:09
gorjangorjan
1,652617
answered Mar 24 at 21:09
gorjangorjan
1,652617
answered Mar 24 at 21:09
gorjangorjan
1,652617
answered Mar 24 at 21:09
gorjangorjan
1,652617
1,652617
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
add a comment |
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
Perfect. Thanks for your help!
– Supratim Haldar
Mar 25 at 5:29
add a comment |
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