整合去雾网页工具

DCP_最好加入后处理/dehaze.py

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+import cv2;
+import math;
+import os
+import numpy as np;
+
+def DarkChannel(im,sz):
+    b,g,r = cv2.split(im)
+    dc = cv2.min(cv2.min(r,g),b);
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(sz,sz))
+    dark = cv2.erode(dc,kernel)
+    return dark
+
+def AtmLight(im,dark):
+    [h,w] = im.shape[:2]
+    imsz = h*w
+    numpx = int(max(math.floor(imsz/1000),1))
+    darkvec = dark.reshape(imsz);
+    imvec = im.reshape(imsz,3);
+
+    indices = darkvec.argsort();
+    indices = indices[imsz-numpx::]
+
+    atmsum = np.zeros([1,3])
+    for ind in range(1,numpx):
+       atmsum = atmsum + imvec[indices[ind]]
+
+    A = atmsum / numpx;
+    return A
+
+def TransmissionEstimate(im,A,sz):
+    omega = 0.95;
+    im3 = np.empty(im.shape,im.dtype);
+
+    for ind in range(0,3):
+        im3[:,:,ind] = im[:,:,ind]/A[0,ind]
+
+    transmission = 1 - omega*DarkChannel(im3,sz);
+    return transmission
+
+def Guidedfilter(im,p,r,eps):
+    mean_I = cv2.boxFilter(im,cv2.CV_64F,(r,r));
+    mean_p = cv2.boxFilter(p, cv2.CV_64F,(r,r));
+    mean_Ip = cv2.boxFilter(im*p,cv2.CV_64F,(r,r));
+    cov_Ip = mean_Ip - mean_I*mean_p;
+
+    mean_II = cv2.boxFilter(im*im,cv2.CV_64F,(r,r));
+    var_I   = mean_II - mean_I*mean_I;
+
+    a = cov_Ip/(var_I + eps);
+    b = mean_p - a*mean_I;
+
+    mean_a = cv2.boxFilter(a,cv2.CV_64F,(r,r));
+    mean_b = cv2.boxFilter(b,cv2.CV_64F,(r,r));
+
+    q = mean_a*im + mean_b;
+    return q;
+
+def TransmissionRefine(im,et):
+    gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY);
+    gray = np.float64(gray)/255;
+    r = 60;
+    eps = 0.0001;
+    t = Guidedfilter(gray,et,r,eps);
+
+    return t;
+
+def Recover(im,t,A,tx = 0.1):
+    res = np.empty(im.shape,im.dtype);
+    t = cv2.max(t,tx);
+
+    for ind in range(0,3):
+        res[:,:,ind] = (im[:,:,ind]-A[0,ind])/t + A[0,ind]
+
+    return res
+
+def getFileList(dir,Filelist, ext=None):
+    """
+    获取文件夹及其子文件夹中文件列表
+    输入 dir：文件夹根目录
+    输入 ext: 扩展名
+    返回： 文件路径列表
+    """
+    newDir = dir
+    if os.path.isfile(dir):
+        if ext is None:
+            Filelist.append(dir)
+        else:
+            if ext in dir[-3:]:
+                Filelist.append(dir)
+    
+    elif os.path.isdir(dir):
+        for s in os.listdir(dir):
+            newDir=os.path.join(dir,s)
+            getFileList(newDir, Filelist, ext)
+ 
+    return Filelist
+
+if __name__ == '__main__':
+    import sys
+
+    sz = 10 # 窗口函数
+    tx = 0.2 # 传输图最小值
+
+    try:
+        local_dir = sys.argv[1]
+    except:
+        local_dir = './image/'
+    
+    try:
+        sz = int(sys.argv[2])
+    except:
+        sz = sz
+
+    try:
+        tx = float(sys.argv[3])
+    except:
+        tx = tx
+
+    def nothing(*argv):
+        pass
+    # 检索文件
+    src_img_folder = os.path.join(local_dir, 'src')
+
+    imglist = getFileList(src_img_folder, [], '')
+    print('本次执行检索到 '+str(len(imglist))+' 张图像\n')
+    
+    for imgpath in imglist:
+        imgname= os.path.splitext(os.path.basename(imgpath))[0]
+        # cv2.IMREAD_GRAYSCALE / cv2.IMREAD_COLOR ： 加载灰色 / 彩色图像
+        src = cv2.imread(imgpath, cv2.IMREAD_COLOR)
+        # 通道归一滑
+        I = src.astype('float64')/255;
+        # 暗通道图像
+        dark = DarkChannel(I,sz=sz);
+        # ？？？
+        A = AtmLight(I,dark);
+        te = TransmissionEstimate(I,A,sz = sz);
+        t = TransmissionRefine(src,te);
+        print(np.shape(src))
+        print(np.shape(dark))
+        print(np.shape(t))
+        J = Recover(I,t,A,tx=tx); # tx传输图的最小值，用于避免过度曝光
+
+        dark_imgdir = os.path.join(local_dir, 'dark/')
+        trans_imgdir = os.path.join(local_dir, 'trans/')
+        result_imgdir = os.path.join(local_dir, 'result/')
+        cv2.imwrite(dark_imgdir + imgname + "_" + str(sz) + "_" + str(tx) + "_dark.png",dark*255);
+        cv2.imwrite(trans_imgdir + imgname + "_" + str(sz) + "_" + str(tx) + "_t.png", t*255);
+        cv2.imwrite(result_imgdir + imgname + "_" + str(sz) + "_" + str(tx) + "_result.png",J*255);
+