Randomly selects a rectangle region in an image and erases its pixels. 'Random Erasing Data Augmentation' by Zhong et al. See https://arxiv.org/pdf/1708.04896.pdf This variant of RandomErasing is intended to be applied to either a batch or single image tensor after
| 23 | |
| 24 | |
| 25 | class RandomErasing: |
| 26 | """ Randomly selects a rectangle region in an image and erases its pixels. |
| 27 | 'Random Erasing Data Augmentation' by Zhong et al. |
| 28 | See https://arxiv.org/pdf/1708.04896.pdf |
| 29 | |
| 30 | This variant of RandomErasing is intended to be applied to either a batch |
| 31 | or single image tensor after it has been normalized by dataset mean and std. |
| 32 | Args: |
| 33 | probability: Probability that the Random Erasing operation will be performed. |
| 34 | min_area: Minimum percentage of erased area wrt input image area. |
| 35 | max_area: Maximum percentage of erased area wrt input image area. |
| 36 | min_aspect: Minimum aspect ratio of erased area. |
| 37 | mode: pixel color mode, one of 'const', 'rand', or 'pixel' |
| 38 | 'const' - erase block is constant color of 0 for all channels |
| 39 | 'rand' - erase block is same per-channel random (normal) color |
| 40 | 'pixel' - erase block is per-pixel random (normal) color |
| 41 | max_count: maximum number of erasing blocks per image, area per box is scaled by count. |
| 42 | per-image count is randomly chosen between 1 and this value. |
| 43 | """ |
| 44 | |
| 45 | def __init__( |
| 46 | self, |
| 47 | probability=0.5, min_area=0.02, max_area=1/3, min_aspect=0.3, max_aspect=None, |
| 48 | mode='const', min_count=1, max_count=None, num_splits=0, device='cuda'): |
| 49 | self.probability = probability |
| 50 | self.min_area = min_area |
| 51 | self.max_area = max_area |
| 52 | max_aspect = max_aspect or 1 / min_aspect |
| 53 | self.log_aspect_ratio = (math.log(min_aspect), math.log(max_aspect)) |
| 54 | self.min_count = min_count |
| 55 | self.max_count = max_count or min_count |
| 56 | self.num_splits = num_splits |
| 57 | self.mode = mode.lower() |
| 58 | self.rand_color = False |
| 59 | self.per_pixel = False |
| 60 | if self.mode == 'rand': |
| 61 | self.rand_color = True # per block random normal |
| 62 | elif self.mode == 'pixel': |
| 63 | self.per_pixel = True # per pixel random normal |
| 64 | else: |
| 65 | assert not self.mode or self.mode == 'const' |
| 66 | self.device = device |
| 67 | |
| 68 | def _erase(self, img, chan, img_h, img_w, dtype): |
| 69 | if random.random() > self.probability: |
| 70 | return |
| 71 | area = img_h * img_w |
| 72 | count = self.min_count if self.min_count == self.max_count else \ |
| 73 | random.randint(self.min_count, self.max_count) |
| 74 | for _ in range(count): |
| 75 | for attempt in range(10): |
| 76 | target_area = random.uniform(self.min_area, self.max_area) * area / count |
| 77 | aspect_ratio = math.exp(random.uniform(*self.log_aspect_ratio)) |
| 78 | h = int(round(math.sqrt(target_area * aspect_ratio))) |
| 79 | w = int(round(math.sqrt(target_area / aspect_ratio))) |
| 80 | if w < img_w and h < img_h: |
| 81 | top = random.randint(0, img_h - h) |
| 82 | left = random.randint(0, img_w - w) |
no outgoing calls
no test coverage detected