I'm doing an experiment with image generation, but my script outputs a binary file, how can I train a model using llama2.c?

[win10ogod]

I'm doing an experiment with image generation, but my script outputs a binary file, how can I train a model using llama2.c?

import cv2
import numpy as np
import os

def image_to_binary(image_path, binary_path):
    # Read the image
    image = cv2.imread(image_path)

    # Convert the image to np.uint16 type
    image_uint16 = image.astype(np.uint16)

    # Get image shape
    height, width, channels = image.shape

    # Save the shape information and the image to a binary file
    with open(binary_path, 'wb') as binary_file:
        # Write the shape information as 3 uint16 numbers
        binary_file.write(np.uint16(height).tobytes())
        binary_file.write(np.uint16(width).tobytes())
        binary_file.write(np.uint16(channels).tobytes())
        # Write the image data
        binary_file.write(image_uint16.tobytes())

def binary_to_image(binary_path, output_image_path):
    # Read the binary file
    with open(binary_path, 'rb') as binary_file:
        # Read the shape information
        height = np.frombuffer(binary_file.read(2), dtype=np.uint16)[0]
        width = np.frombuffer(binary_file.read(2), dtype=np.uint16)[0]
        channels = np.frombuffer(binary_file.read(2), dtype=np.uint16)[0]
        # Read the image data
        image_data = binary_file.read()
    
    # Convert the binary data back to np.uint16 type array
    image_uint16 = np.frombuffer(image_data, dtype=np.uint16)

    # Reshape the array to the original image shape
    image_array = image_uint16.reshape((height, width, channels))

    # Convert the array to an 8-bit image before saving (if needed)
    image_array_8bit = image_array.astype(np.uint8)

    # Save the image
    cv2.imwrite(output_image_path, image_array_8bit)

def batch_process(input_folder, output_folder_bin, output_folder_images):
    # Ensure the output folders exist
    if not os.path.exists(output_folder_bin):
        os.makedirs(output_folder_bin)
    if not os.path.exists(output_folder_images):
        os.makedirs(output_folder_images)
    
    # Iterate through all image files in the folder
    for filename in os.listdir(input_folder):
        if filename.lower().endswith(('.jpg', '.png', '.jpeg')):  # Handle common image formats
            print(f"Processing {filename}...")
            image_path = os.path.join(input_folder, filename)
            base_filename = os.path.splitext(filename)[0]
            binary_path = os.path.join(output_folder_bin, base_filename + '.bin')
            output_image_path = os.path.join(output_folder_images, filename)
            
            # Image to binary
            image_to_binary(image_path, binary_path)
            
            # Binary to image
            binary_to_image(binary_path, output_image_path)

# Example use
input_folder = 'D:/llama2.c-master/1/images'
output_folder_bin = 'D:/llama2.c-master/1/bin'
output_folder_images = 'D:/llama2.c-master/1/imagesout'

batch_process(input_folder, output_folder_bin, output_folder_images)

@karpathy Can you help?