(sample_size, image_ratio=[], all_choices=False, rng=None)
| 82 | |
| 83 | |
| 84 | def get_random_downsample_ratio(sample_size, image_ratio=[], all_choices=False, rng=None): |
| 85 | def _create_special_list(length): |
| 86 | if length == 1: |
| 87 | return [1.0] |
| 88 | if length >= 2: |
| 89 | first_element = 0.75 |
| 90 | remaining_sum = 1.0 - first_element |
| 91 | other_elements_value = remaining_sum / (length - 1) |
| 92 | special_list = [first_element] + [other_elements_value] * (length - 1) |
| 93 | return special_list |
| 94 | |
| 95 | if sample_size >= 1536: |
| 96 | number_list = [1, 1.25, 1.5, 2, 2.5, 3] + image_ratio |
| 97 | elif sample_size >= 1024: |
| 98 | number_list = [1, 1.25, 1.5, 2] + image_ratio |
| 99 | elif sample_size >= 768: |
| 100 | number_list = [1, 1.25, 1.5] + image_ratio |
| 101 | elif sample_size >= 512: |
| 102 | number_list = [1] + image_ratio |
| 103 | else: |
| 104 | number_list = [1] |
| 105 | |
| 106 | if all_choices: |
| 107 | return number_list |
| 108 | |
| 109 | number_list_prob = np.array(_create_special_list(len(number_list))) |
| 110 | if rng is None: |
| 111 | return np.random.choice(number_list, p=number_list_prob) |
| 112 | else: |
| 113 | return rng.choice(number_list, p=number_list_prob) |
| 114 | |
| 115 | |
| 116 | def resize_mask(mask, latent, process_first_frame_only=True): |
nothing calls this directly
no test coverage detected