Replies: 1 comment 2 replies
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Hello,
Make sure you include the color channels in your shape. It is 3 (for RGB)
if the images are colored or 1 if the images are in greyscale.
On Tue, Jul 19, 2022 at 4:09 PM reshma93s ***@***.***> wrote:
I am getting an error where the data is batched and pre-processed.
Map preprocessing function to training data (and paralellize)
train_data = train_data.map(map_func=preprocess_img,
num_parallel_calls=tf.data.AUTOTUNE)
Shuffle train_data and turn it into batches and prefetch it (load it
faster)
train_data =
train_data.shuffle(buffer_size=1000).batch(batch_size=32).prefetch(buffer_size=tf.data.AUTOTUNE)
Error:-
------------------------------
ValueError Traceback (most recent call last)
<https://localhost:8080/#> in ()
1 # Map preprocessing function to training data (and paralellize)
----> 2 train_data = train_data.map(map_func=preprocess_img,
num_parallel_calls=tf.data.AUTOTUNE)
3 # Shuffle train_data and turn it into batches and prefetch it (load it
faster)
4 train_data =
train_data.shuffle(buffer_size=1000).batch(batch_size=32).prefetch(buffer_size=tf.data.AUTOTUNE)
10 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py
<https://localhost:8080/#> in wrapper(*args, **kwargs)
690 except Exception as e: # pylint:disable=broad-except
691 if hasattr(e, 'ag_error_metadata'):
--> 692 raise e.ag_error_metadata.to_exception(e)
693 else:
694 raise
ValueError: in user code:
File "<ipython-input-20-16eda5b2fbee>", line 6, in preprocess_img *
image = tf.image.resize(image,[img_shape,img_shape])
ValueError: 'images' must have either 3 or 4 dimensions.
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I am getting an error where the data is batched and pre-processed.
Map preprocessing function to training data (and paralellize)
train_data = train_data.map(map_func=preprocess_img, num_parallel_calls=tf.data.AUTOTUNE)
Shuffle train_data and turn it into batches and prefetch it (load it faster)
train_data = train_data.shuffle(buffer_size=1000).batch(batch_size=32).prefetch(buffer_size=tf.data.AUTOTUNE)
Error:-
ValueError Traceback (most recent call last)
in ()
1 # Map preprocessing function to training data (and paralellize)
----> 2 train_data = train_data.map(map_func=preprocess_img, num_parallel_calls=tf.data.AUTOTUNE)
3 # Shuffle train_data and turn it into batches and prefetch it (load it faster)
4 train_data = train_data.shuffle(buffer_size=1000).batch(batch_size=32).prefetch(buffer_size=tf.data.AUTOTUNE)
10 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/autograph/impl/api.py in wrapper(*args, **kwargs)
690 except Exception as e: # pylint:disable=broad-except
691 if hasattr(e, 'ag_error_metadata'):
--> 692 raise e.ag_error_metadata.to_exception(e)
693 else:
694 raise
ValueError: in user code:
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