np.ndarray: The output image with added fog, as a numpy array. Raises: ValueError: If the input image's dtype is not uint8 or float32. Reference: https://github.com/UjjwalSaxena/Automold--Road-Augmentation-Libr
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 - albumentations/albumentations/augmentations/transforms.py at main · albumentations-team/albumentations
pytorch Albumentations返回“KeyError：'标签'首先要知道你的错误不是数据类型不是int 64;那就是'labels'...
pytorch Albumentations返回“KeyError：'标签'首先要知道你的错误不是数据类型不是int 64;那就是'labels'...
assert self.lower >= 0, "contrast lower must be non-negative." def __call__(self, image, boxes=None, labels=None): if random.randint(2): print('saturation') image[:, :, 1] *= random.uniform(self.lower, self.upper) # 已知 S 的范围是在 (0, 1)之间 image[:, :, 1] = np...
msg = "high_shift must be in range [0, 1]" raise ValueError(msg) if input_dtype != np.uint8: raise ValueError(f"Unsupported image type {input_dtype}") if input_dtype in [np.float32, np.float64, np.float16]: img = from_float(img, dtype=np.uint8) needs_float = True t ...
1440 1435 return new_image 1441 1436 1442 1437 1443 - def bbox_from_mask(mask: np.ndarray) -> tuple[int, int, int, int]: 1444 - """Create bounding box from binary mask (fast version) 1445 - 1446 - Args: 1447 - mask (numpy.ndarray): binary mask. 1448 - 1449 - ...
array(mean, dtype=np.float32) mean_np *= max_pixel_value Expand All @@ -120,7 +119,7 @@ def normalize(img: np.ndarray, mean: ColorType, std: ColorType, max_pixel_value: return normalize_numpy(img, mean_np, denominator) @preserve_shape @preserve_channel_dim def normalize_per_i...
beta_limit: ScaleFloatType = (0, 0.1), read_fn: Callable[[Any], np.ndarray] = read_rgb_image, always_apply: bool = False, always_apply: Optional[bool] = None, p: float = 0.5, ): super().__init__(always_apply=always_apply, p=p) Expand Down Expand Up @@ -274,7 +274,7...