自适应二值化（扫描全能王的增强锐化）

src/adathres.py

+# coding: utf-8
+
+# 自适应二值化（扫描全能王的增强锐化）
+# python adathres.py <file|dir>
+
+import numpy as np
+from scipy import signal
+import cv2
+import re
+import os
+from os import path
+import sys
+
+def adaptive_thres(img, win, beta=0.9):
+    if win % 2 == 0: win = win - 1
+    # 边界的均值有点麻烦
+    # 这里分别计算和和邻居数再相除
+    kern = np.ones([win, win])
+    sums = signal.correlate2d(img, kern, 'same')
+    cnts = signal.correlate2d(np.ones_like(img), kern, 'same')
+    means = sums // cnts
+    # 如果直接采用均值作为阈值，背景会变花
+    # 但是相邻背景颜色相差不大
+    # 所以乘个系数把它们过滤掉
+    img = np.where(img < means * beta, 0, 255)
+    return img
+
+def process_file(fname):
+    if not fname.endswith('.png') and \
+       not fname.endswith('.jpg') and \
+       not fname.endswith('.gif'):
+        return
+        
+    print(fname)
+    img = cv2.imread(fname, cv2.IMREAD_GRAYSCALE)
+    img = adaptive_thres(img, 9)
+    os.unlink(fname)
+    nfname = re.sub(r'\.\w+$', '', fname) + '.png'
+    cv2.imwrite(nfname, img, [cv2.IMWRITE_PNG_BILEVEL, 1])
+    
+def procee_dir(dir):
+    files = os.listdir(dir)
+    for fname in files:
+        fname = path.join(dir, fname)
+        process_file(fname)
+        
+def main():
+    fname = sys.argv[1]
+    if path.isdir(fname):
+        procee_dir(fname)
+    else:
+        process_file(fname)
+        
+if __name__ == '__main__': main()