init + inference.py патч

data/preprocess/crop_merge_image.py

@@ -0,0 +1,142 @@
+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)