在运行的过程依据传入的不同参数BasicTransform的__call__方法会调用PadIfNeeded中不同方法,image参数会调用applay方法,mask参数会调用apply_to_mask方法。 裁剪与中心裁剪(Crop & CenterCrop) 上面我们使用了PadIfNeeded对图片进行了填充,想要恢复原始的大小这时候就可以使用相关的裁剪方法:CenterCrop、Crop等类。 先来...
f'{save_fig_name}.png', dpi=120)plt.show()原图 1. CenterCrop def center_crop(img):height, width = img.shape[:2]plt.figure(figsize=(16,9))for i in range(8):plt.subplot(4, 2, i+1)crop_height, crop_width = np.random.randint(100, height), np.random.randint(100, width)
CenterCrop and Crop 中心裁剪,裁剪。 这里用了crop来恢复之前的大小 代码语言:javascript 复制 aug=A.CenterCrop(p=1,height=original_height,width=original_width)augmented=aug(image=image_padded,mask=mask_padded)image_center_cropped=augmented['image']mask_center_cropped=augmented['mask']print(image_center...
padded_constant_image = F.pad(image, min_height=512, min_width=512, border_mode=cv2.BORDER_CONSTANT) cropped_image = F.center_crop(image, crop_height=256, crop_width=256) figure, ax = plt.subplots(nrows=1, ncols=5, figsize=(18, 10)) ax.ravel()[0].imshow(image) ax.ravel()[0...
CenterCrop 和 Crop: 代码语言:javascript 复制 aug = CenterCrop(p=1, height=original_height, width=original_width) augmented = aug(image=image_padded, mask=mask_padded) image_center_cropped = augmented['image'] mask_center_cropped = augmented['mask'] print(image_center_cropped.shape, mask_cente...
CenterCrop 和 Crop: aug = CenterCrop(p=1, height=original_height, width=original_width) augmented = aug(image=image_padded, mask=mask_padded) image_center_cropped = augmented['image'] mask_center_cropped = augmented['mask'] print(image_center_cropped.shape, mask_center_cropped.shape) assert...
.cvtColor(image,cv2.COLOR_BGR2RGB)resized_image=F.resize(image,height=256,width=256)padded_image=F.pad(image,min_height=512,min_width=512)padded_constant_image=F.pad(image,min_height=512,min_width=512,border_mode=cv2.BORDER_CONSTANT)cropped_image=F.center_crop(image,crop_height=256,crop_...
return F.center_crop(img, self.height, self.width) return fcrops.center_crop(img, self.height, self.width) def apply_to_bbox(self, bbox: BoxInternalType, **params: Any) -> BoxInternalType: return F.bbox_center_crop(bbox, self.height, self.width, **params) return fcrops.bbox...
medium=A.Compose([ A.HorizontalFlip(p=1), A.RandomSizedCrop((800 - 100, 800 + 100), 600, 600), A.MotionBlur(blur_limit=37, p=1), ], bbox_params={'format':'coco',
yolo:[x_center, y_center, width, height]并进行归一化,在上图中是[0.4046875, 0.840625, 0.503125, 0.24375] Albumentations支持同时对标注和图像进行变换: import albumentations as A import cv2 transform = A.Compose([ A.RandomCrop(width=450, height=450), ...