Custom preprocessing_function with tf.image.rgb_to_grayscale - ValueError: setting an array element with a...
I am trying to use a custom preprocessing function to convert RGB images to grayscale during training. As such, I try to use tf.image.rbg_to_grayscale for this. My function looks as following:
def prep_data(x):
x = tf.image.rgb_to_grayscale(x)
return x
datagen = ImageDataGenerator(preprocessing_function=prep_data,validation_split=0.15)
The train_generator is defined using datagen.flow_from_dataframe(...). Training without this custom function works just fine, however once I use it I get the following error:
ValueError: setting an array element with a sequence.
Judging from this answer here, I assume I need to change my input to rgb_to_grayscale, but I don't know what's the correct way of passing x to the function.
Any idea on how to solve this?
python tensorflow keras image-preprocessing
edited Nov 22 '18 at 10:15
today
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
add a comment |
I am trying to use a custom preprocessing function to convert RGB images to grayscale during training. As such, I try to use tf.image.rbg_to_grayscale for this. My function looks as following:
def prep_data(x):
x = tf.image.rgb_to_grayscale(x)
return x
datagen = ImageDataGenerator(preprocessing_function=prep_data,validation_split=0.15)
The train_generator is defined using datagen.flow_from_dataframe(...). Training without this custom function works just fine, however once I use it I get the following error:
ValueError: setting an array element with a sequence.
Judging from this answer here, I assume I need to change my input to rgb_to_grayscale, but I don't know what's the correct way of passing x to the function.
Any idea on how to solve this?
python tensorflow keras image-preprocessing
edited Nov 22 '18 at 10:15
today
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56
add a comment |
I am trying to use a custom preprocessing function to convert RGB images to grayscale during training. As such, I try to use tf.image.rbg_to_grayscale for this. My function looks as following:
def prep_data(x):
x = tf.image.rgb_to_grayscale(x)
return x
datagen = ImageDataGenerator(preprocessing_function=prep_data,validation_split=0.15)
The train_generator is defined using datagen.flow_from_dataframe(...). Training without this custom function works just fine, however once I use it I get the following error:
ValueError: setting an array element with a sequence.
Judging from this answer here, I assume I need to change my input to rgb_to_grayscale, but I don't know what's the correct way of passing x to the function.
Any idea on how to solve this?
python tensorflow keras image-preprocessing
edited Nov 22 '18 at 10:15
today
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
I am trying to use a custom preprocessing function to convert RGB images to grayscale during training. As such, I try to use tf.image.rbg_to_grayscale for this. My function looks as following:
def prep_data(x):
x = tf.image.rgb_to_grayscale(x)
return x
datagen = ImageDataGenerator(preprocessing_function=prep_data,validation_split=0.15)
The train_generator is defined using datagen.flow_from_dataframe(...). Training without this custom function works just fine, however once I use it I get the following error:
ValueError: setting an array element with a sequence.
Judging from this answer here, I assume I need to change my input to rgb_to_grayscale, but I don't know what's the correct way of passing x to the function.
Any idea on how to solve this?
python tensorflow keras image-preprocessing
python tensorflow keras image-preprocessing
edited Nov 22 '18 at 10:15
today
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
edited Nov 22 '18 at 10:15
today
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
edited Nov 22 '18 at 10:15
today
10.8k21837
edited Nov 22 '18 at 10:15
today
10.8k21837
edited Nov 22 '18 at 10:15
today
10.8k21837
10.8k21837
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
asked Nov 21 '18 at 22:26
AaronDTAaronDT
8902526
8902526
If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56
add a comment |
If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56
If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56
If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56
add a comment |
1 Answer
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Instead, you can use the color_mode argument of flow_from_directory and set it to 'grayscale' to convert the images to grayscale. From Keras docs:
color_mode: One of "grayscale", "rbg", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
add a comment |
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Instead, you can use the color_mode argument of flow_from_directory and set it to 'grayscale' to convert the images to grayscale. From Keras docs:
color_mode: One of "grayscale", "rbg", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
add a comment |
Instead, you can use the color_mode argument of flow_from_directory and set it to 'grayscale' to convert the images to grayscale. From Keras docs:
color_mode: One of "grayscale", "rbg", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
add a comment |
Instead, you can use the color_mode argument of flow_from_directory and set it to 'grayscale' to convert the images to grayscale. From Keras docs:
color_mode: One of "grayscale", "rbg", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
Instead, you can use the color_mode argument of flow_from_directory and set it to 'grayscale' to convert the images to grayscale. From Keras docs:
color_mode: One of "grayscale", "rbg", "rgba". Default: "rgb". Whether the images will be converted to have 1, 3, or 4 channels.
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
answered Nov 22 '18 at 10:10
todaytoday
10.8k21837
10.8k21837
add a comment |
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If the answer resolved your issue, kindly accept it by clicking on the checkmark next to the answer to mark it as "answered" - see What should I do when someone answers my question?
– today
Nov 26 '18 at 15:56