|
|
| def find_closest_aspect_ratio(aspect_ratio, target_ratios, width, height, |
| image_size): |
| best_ratio_diff = float('inf') |
| best_ratio = (1, 1) |
| area = width * height |
| for ratio in target_ratios: |
| target_aspect_ratio = ratio[0] / ratio[1] |
| ratio_diff = abs(aspect_ratio - target_aspect_ratio) |
| if ratio_diff < best_ratio_diff: |
| best_ratio_diff = ratio_diff |
| best_ratio = ratio |
| elif ratio_diff == best_ratio_diff: |
| if area > 0.5 * image_size * image_size * ratio[0] * ratio[1]: |
| best_ratio = ratio |
| return best_ratio |
|
|
| def dynamic_preprocess(image, |
| min_num=1, |
| max_num=6, |
| image_size=448, |
| use_thumbnail=False): |
| orig_width, orig_height = image.size |
| aspect_ratio = orig_width / orig_height |
|
|
| |
| target_ratios = {(i, j) |
| for n in range(min_num, max_num + 1) |
| for i in range(1, n + 1) for j in range(1, n + 1) |
| if i * j <= max_num and i * j >= min_num} |
| target_ratios = sorted(target_ratios, key=lambda x: x[0] * x[1]) |
|
|
| |
| target_aspect_ratio = find_closest_aspect_ratio(aspect_ratio, |
| target_ratios, orig_width, |
| orig_height, image_size) |
|
|
| |
| target_width = image_size * target_aspect_ratio[0] |
| target_height = image_size * target_aspect_ratio[1] |
| blocks = target_aspect_ratio[0] * target_aspect_ratio[1] |
|
|
| |
| resized_img = image.resize((target_width, target_height)) |
| processed_images = [] |
| for i in range(blocks): |
| box = ((i % (target_width // image_size)) * image_size, |
| (i // (target_width // image_size)) * image_size, |
| ((i % (target_width // image_size)) + 1) * image_size, |
| ((i // (target_width // image_size)) + 1) * image_size) |
| |
| split_img = resized_img.crop(box) |
| processed_images.append(split_img) |
| assert len(processed_images) == blocks |
| if use_thumbnail and len(processed_images) != 1: |
| thumbnail_img = image.resize((image_size, image_size)) |
| processed_images.append(thumbnail_img) |
| return processed_images |
