convert jpeg to mnist bibary file in python

To convert a JPEG image to the binary format used by the MNIST dataset in Python, you can follow these steps:

1. Import the necessary libraries:

main.py
import os
import numpy as np
from PIL import Image
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2. Load the JPEG image using the PIL library:

main.py
img = Image.open('input.jpg')
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3. Resize the image to 28x28 pixels to match the MNIST dataset size:

main.py
img = img.resize((28, 28))
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4. Convert the image to grayscale:

main.py
img = img.convert('L')
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5. Normalize the pixel values to be between 0 and 1:

main.py
img = np.array(img)
img = img / 255.0
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6. Generate the binary file in the MNIST format:

main.py
header = np.array([0x00000803, 1, 28, 28], dtype='>i4')
data = np.expand_dims(img, axis=0)
data = np.packbits(data, axis=-1, bitorder='>', count=28*28)
data = np.concatenate(header, data).tobytes()

with open('output', 'wb') as f:
    f.write(data)
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Make sure to replace 'input.jpg' with the path to your input JPEG image, and 'output' with the desired path for the generated binary file.

Note: The MNIST dataset uses a specific binary format, where the first 4 bytes represent the magic number, the second 4 bytes represent the number of images, and the remaining bytes represent the pixel values in sequential order.