Pix2pix: Image-to-image translation with a conditional GAN

[btb4198]

So I am trying to do this tutorials but I want to use my own dataset. I am having problems "Build an input pipeline with tf.data."
My question is about their code:

def load_image_train(image_file):
  input_image, real_image = load(image_file)
  input_image, real_image = random_jitter(input_image, real_image)
  input_image, real_image = normalize(input_image, real_image)

  return input_image, real_image

train_dataset = tf.data.Dataset.list_files(str(PATH / 'train/*.jpg'))
train_dataset = train_dataset.map(load_image_train,
                                  num_parallel_calls=tf.data.AUTOTUNE)
train_dataset = train_dataset.shuffle(BUFFER_SIZE)
train_dataset = train_dataset.batch(BATCH_SIZE)

when they call load_image_train, are they sending a list of images or just one image?
I am really not liking this Not displaying type stuff

 

[Mark44]

So I am trying to do this tutorials but I want to use my own dataset. I am having problems "Build an input pipeline with tf.data."
My question is about their code:

def load_image_train(image_file):
  input_image, real_image = load(image_file)
  input_image, real_image = random_jitter(input_image, real_image)
  input_image, real_image = normalize(input_image, real_image)

  return input_image, real_image

train_dataset = tf.data.Dataset.list_files(str(PATH / 'train/*.jpg'))
train_dataset = train_dataset.map(load_image_train,
                                  num_parallel_calls=tf.data.AUTOTUNE)
train_dataset = train_dataset.shuffle(BUFFER_SIZE)
train_dataset = train_dataset.batch(BATCH_SIZE)

when they call load_image_train, are they sending a list of images or just one image?
I am really not liking this Not displaying type stuff

What looks to me like what's happening is that load_image_train has a single image file as its input, but returns two image files: input_image and real_image.

 

[PeterDonis]

when they call load_image_train, are they sending a list of images or just one image?

The load_image_train function takes a single image filename as its argument.

The effect of the map method call is to call load_image_train once for each filename in a list of filenames returned by the list_files method call.

 

[btb4198]

I am getting a very weird error when I am trying to Build an input pipeline with tf.data. I am combining my reference image and my drawing into a tuple. Then I added to that to list. This should work,
but now I am getting this weird error at this line:
train_dataset = train_dataset.map(load_image_train, num_parallel_calls=tf.data.AUTOTUNE)

Here is my code:

@tf.function()
def load_image_train(a_training_datapoint):
 print(type(a_training_datapoint))
 print("here 1")
 real_image_path, drawing_path = zip(*a_training_datapoint)
 print("here 2")
 real_image = convert_images_to_tensor(real_image_path)
 print("here 3")
 drawing_image = convert_images_to_tensor(drawing_path)
 real_image, drawing_image = random_jitter(real_image, drawing_image)
 real_image, drawing_image = normalize(real_image, drawing_image)
return real_image, drawing_image

and then I have this:

test_dataset_list = []
for data in test_set:
 test_dataset_list.append(zip(data.reference_image, data.drawing))
print(test_dataset_list)

Here 1 is the only one that prints out.

so it seem to not like how I am unzipping my tuple, but I am sure I am doing it right.

Also it say this : <class 'tensorflow.python.framework.ops.Tensor'>

when I am printing out the type for the a_test_datapoint