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Zero
Running
on
Zero
File size: 4,605 Bytes
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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)
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