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# grids = [create_grid(generated_batch[j]) for j in range(len(generated_batch))] | |
# save_as_gif_animation(grids, output_animation_path) | |
import math | |
import numpy as np | |
from PIL import Image | |
def create_grid(image_arrays: np.ndarray): | |
batch_size = image_arrays.shape[0] | |
image_height = image_arrays.shape[1] | |
image_width = image_arrays.shape[2] | |
n_channels = image_arrays.shape[3] | |
n_cols = n_rows = math.ceil(batch_size**0.5) | |
n_samples = min(n_rows * n_cols, batch_size) | |
canvas_height = image_height * n_rows | |
canvas_width = image_width * n_cols | |
canvas = np.zeros((canvas_height, canvas_width, n_channels)) | |
for i in range(n_samples): | |
row = i // n_cols | |
col = i % n_rows | |
canvas[ | |
row * image_height : (row + 1) * image_height, | |
col * image_width : (col + 1) * image_width, | |
:, | |
] = image_arrays[i] | |
return canvas | |
def save_as_gif_animation(images, file_path): | |
channels = images.shape[-1] | |
if channels == 1: | |
images = [img.squeeze() for img in images] | |
Image.fromarray(images[0]).save( | |
file_path, | |
save_all=True, | |
duration=10, | |
append_images=[Image.fromarray(arr) for arr in images[1:]], | |
loop=1, | |
) |
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