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