CODEWITHSUNDEEP
machine-learningtensorflow
Zan Huang
Zan Huang

Reputation: 663

How do I create a dataset with multiple images the same format as CIFAR10?

I have images 1750*1750 and I would like to label them and put them into a file in the same format as CIFAR10. I have seen a similar answer before that gave an answer:

label = [3]
im = Image.open(img)
im = (np.array(im))
print(im)

r = im[:,:,0].flatten()
g = im[:,:,1].flatten()
b = im[:,:,2].flatten()
array = np.array(list(label) + list(r) + list(g) + list(b), np.uint8)

array.tofile("info.bin")

but it doesn't include how to add multiple images in a single file. I have looked at CIFAR10 and tried to append the arrays in the same way, but all I got was the following error:

E tensorflow/core/client/tensor_c_api.cc:485] Read less bytes than requested

Note that I am using Tensorflow to do my computations, and I have been able to isolate the problem from the data.

Upvotes: 0

Views: 787

Answers (1)

mrry
mrry

Reputation: 126184

The CIFAR-10 binary format represents each example as a fixed-length record with the following format:

  • 1-byte label.
  • 1 byte per pixel for the red channel of the image.
  • 1 byte per pixel for the green channel of the image.
  • 1 byte per pixel for the blue channel of the image.

Assuming you have a list of image filenames called images, and a list of integers (less than 256) called labels corresponding to their labels, the following code would write a single file containing these images in CIFAR-10 format:

with open(output_filename, "wb") as f:
  for label, img in zip(labels, images): 
    label = np.array(label, dtype=np.uint8)
    f.write(label.tostring())  # Write label.

    im = np.array(Image.open(img), dtype=np.uint8)
    f.write(im[:, :, 0].tostring())  # Write red channel.
    f.write(im[:, :, 1].tostring())  # Write green channel.
    f.write(im[:, :, 2].tostring())  # Write blue channel.

Upvotes: 2

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