Spaces:
Sleeping
Sleeping
| 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 | |
| import re | |
| def find_seg_indices(text): | |
| all_seg_indices = [m.start() for m in re.finditer(r'\[SEG\]', text)] | |
| answer_spans = [(m.start(), m.end()) for m in re.finditer(r'<answer>.*?</answer>', text, re.DOTALL)] | |
| if len(answer_spans) == 0: | |
| return [], [] | |
| if len(answer_spans) > 1: | |
| print(f"Warning: There should be only one <answer> tag in the text. {text}") | |
| answer_span = answer_spans[0] | |
| start, end = answer_span | |
| seg_indices_in_reason = [] | |
| seg_indices_in_answer = [] | |
| for idx, seg_ind in enumerate(all_seg_indices): | |
| if start <= seg_ind < end: | |
| seg_indices_in_answer.append(idx) | |
| elif seg_ind < start: | |
| seg_indices_in_reason.append(idx) | |
| else: | |
| continue | |
| return seg_indices_in_reason, seg_indices_in_answer |