import os import cv2 import numpy as np # SIZE =256 # BATCH_SIZE = 32 # STRIDES = 256 def split_img(img, size_x, size_y, strides): max_y, max_x = img.shape[:2] border_y = 0 if max_y % size_y != 0: border_y = size_y - (max_y % size_y) img = cv2.copyMakeBorder(img,border_y,0,0,0,cv2.BORDER_REPLICATE) # img = cv2.copyMakeBorder(img, border_y, 0, 0, 0, cv2.BORDER_CONSTANT, value=[255,255,255]) border_x = 0 if max_x % size_x != 0: border_x = size_x - (max_x % size_x) # img = cv2.copyMakeBorder(img, 0, 0, border_x, 0, cv2.BORDER_CONSTANT, value=[255,255,255]) img = cv2.copyMakeBorder(img,0,0,border_x,0,cv2.BORDER_REPLICATE) # h,w max_y, max_x = img.shape[:2] parts = [] curr_y = 0 x = 0 y = 0 # TODO: rewrite with generators. while (curr_y + size_y) <= max_y: curr_x = 0 while (curr_x + size_x) <= max_x: parts.append(img[curr_y:curr_y + size_y, curr_x:curr_x + size_x]) curr_x += strides y += 1 curr_y += strides # parts is a list # (windows_number_x*windows_number_y,SIZE,SIZE,3) # print(max_y,max_x) # print(y,x) # print(np.array(parts).shape) return parts, border_x, border_y, max_x, max_y def combine_imgs(border_x,border_y,imgs, max_y, max_x,size_x, size_y, strides): # weighted_img index = int(size_x / strides) weight_img = np.ones(shape=(max_y,max_x)) weight_img[0:strides] = index weight_img[-strides:] = index weight_img[:,0:strides]=index weight_img[:,-strides:]=index # 边上 i = 0 for j in range(1,index+1): # 左上 weight_img[0:strides,i:i+strides] = np.ones(shape=(strides,strides))*j weight_img[i:i+strides,0:strides] = np.ones(shape=(strides,strides))*j # 右上 weight_img[i:i+strides,-strides:] = np.ones(shape=(strides,strides))*j if i == 0: weight_img[0:strides,-strides:] = np.ones(shape=(strides,strides))*j else: weight_img[0:strides,-strides-i:-i] = np.ones(shape=(strides,strides))*j # 左下 weight_img[-strides:,i:i+strides] = np.ones(shape=(strides,strides))*j if i == 0: weight_img[-strides:,0:strides] = np.ones(shape=(strides,strides))*j else: weight_img[-strides-i:-i:,0:strides] = np.ones(shape=(strides,strides))*j # 右下 if i == 0: weight_img[-strides:,-strides:] = np.ones(shape=(strides,strides))*j else: weight_img[-strides-i:-i,-strides:] = np.ones(shape=(strides,strides))*j weight_img[-strides:,-strides-i:-i] = np.ones(shape=(strides,strides))*j i += strides for i in range(strides,max_y-strides,strides): for j in range(strides,max_x-strides,strides): weight_img[i:i+strides,j:j+strides] = np.ones(shape=(strides,strides))*weight_img[i][0]*weight_img[0][j] if len(imgs[0].shape)==2: new_img = np.zeros(shape=(max_y,max_x)) weight_img = (1 / weight_img) else: new_img = np.zeros(shape=(max_y,max_x,imgs[0].shape[-1])) weight_img = (1 / weight_img).reshape((max_y,max_x,1)) weight_img = np.tile(weight_img,(1,1,imgs[0].shape[-1])) curr_y = 0 x = 0 y = 0 i = 0 # TODO: rewrite with generators. while (curr_y + size_y) <= max_y: curr_x = 0 while (curr_x + size_x) <= max_x: new_img[curr_y:curr_y + size_y, curr_x:curr_x + size_x] += weight_img[curr_y:curr_y + size_y, curr_x:curr_x + size_x]*imgs[i] i += 1 curr_x += strides y += 1 curr_y += strides new_img = new_img[border_y:, border_x:] # print(border_y,border_x) return new_img def stride_integral(img,stride=32): h,w = img.shape[:2] if (h%stride)!=0: padding_h = stride - (h%stride) img = cv2.copyMakeBorder(img,padding_h,0,0,0,borderType=cv2.BORDER_REPLICATE) else: padding_h = 0 if (w%stride)!=0: padding_w = stride - (w%stride) img = cv2.copyMakeBorder(img,0,0,padding_w,0,borderType=cv2.BORDER_REPLICATE) else: padding_w = 0 return img,padding_h,padding_w def mkdir_s(path: str): """Create directory in specified path, if not exists.""" if not os.path.exists(path): os.makedirs(path) if __name__ =='__main__': parts, border_x, border_y, max_x, max_y = split_img(im,512,512,strides=512) result = combine_imgs(border_x,border_y,parts, max_y, max_x,512, 512, 512)