Initial commit

Author: irfanICMLL

.idea/code.iml

@@ -0,0 +1,158 @@
+from PIL import Image, ImageEnhance, ImageFilter
+from pylab import *
+# import numpy as np
+from scipy.ndimage import filters
+# from skimage import io
+import glob, os
+
+in_dir = 'pic_org'
+out_dir = 'pic_color'
+if not os.path.exists(out_dir): os.mkdir(out_dir)
+
+
+class MyGaussianBlur(ImageFilter.Filter):
+    name = "GaussianBlur"
+
+    def __init__(self, radius=2, bounds=None):
+        self.radius = radius
+        self.bounds = bounds
+
+    def filter(self, image):
+        if self.bounds:
+            clips = image.crop(self.bounds).gaussian_blur(self.radius)
+            image.paste(clips, self.bounds)
+            return image
+        else:
+            return image.gaussian_blur(self.radius)
+
+
+def start(mat):
+    w, h, c = mat.shape
+    ws = int(w * random(1))
+    hs = int(h * random(1))
+    while (mat[ws, hs, 0] > 254) and (mat[ws, hs, 1] > 254) and (mat[ws, hs, 2] > 254):
+        ws = int(w * random(1))
+        hs = int(h * random(1))
+    return ws, hs
+
+
+def gen_color_line(mat, dir,max_length,max_dif):
+    w, h, c = mat.shape
+    ws = int(w * random(1))
+    hs = int(h * random(1))
+    while (mat[ws, hs, 0] > 254) and (mat[ws, hs, 1] > 254) and (mat[ws, hs, 2] > 254):
+        ws = int(w * random(1))
+        hs = int(h * random(1))
+    if dir == 1:
+        wt = ws
+        ht = hs
+        while (wt < w - 1) and (abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                        int(mat[wt + 1, ht, 1]) + int(mat[wt + 1, ht, 2]) + int(mat[wt + 1, ht, 0]))) < 80):
+            wt = wt + 1
+    if dir == 2:
+        wt = ws
+        ht = hs
+        while (ht < h - 1) and (abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                        int(mat[wt, ht + 1, 1]) + int(mat[wt, ht + 1, 2]) + int(mat[wt, ht + 1, 0]))) < 3):
+            ht = ht + 1
+    if dir == 3:
+        wt = ws
+        ht = hs
+        length = 0
+        while (length < max_length) and (wt < w-1) and (ht < h-1) and (
+            abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                            int(mat[wt + 1, ht + 1, 1]) + int(mat[wt + 1, ht + 1, 2]) + int(
+                        mat[wt + 1, ht + 1, 0]))) < max_dif):
+            ht += 1
+            wt += 1
+            length = abs(wt - ws) + abs(ht - hs)
+    return ws, hs, wt, ht, length
+
+
+def main():
+    
+    count = 0
+    #parameter
+    wsize = 1024  # double the resolution
+    Gamma = 0.97
+    Phi = 200
+    Epsilon = 0.1
+    k = 2
+    Sigma = 1.5
+    max_length=20
+    min_length=10
+    max_dif=30
+    n_point=50
+    dir = 3
+
+    input_paths = glob.glob(in_dir+ '/*.jpg')	
+    input_paths+=(glob.glob(in_dir+ '/*.jpeg'))
+    input_paths+=(glob.glob(in_dir+ '/*.png'))
+    for files1 in input_paths:
+        filepath, filename = os.path.split(files1)
+
+        im = Image.open(files1).convert('L')
+        im = array(ImageEnhance.Sharpness(im).enhance(3.0))
+        im2 = filters.gaussian_filter(im, Sigma)
+        im3 = filters.gaussian_filter(im, Sigma * k)
+        differencedIm2 = im2 - (Gamma * im3)
+        (x, y) = shape(im2)
+        for i in range(x):
+            for j in range(y):
+                if differencedIm2[i, j] < Epsilon:
+                    differencedIm2[i, j] = 1
+                else:
+                    differencedIm2[i, j] = 250 + tanh(Phi * (differencedIm2[i, j]))
+
+
+        gray_pic = differencedIm2.astype(np.uint8)
+        color_pic = Image.open(files1)
+        real = np.atleast_2d(color_pic)
+        
+        
+        if real.ndim == 3:
+            w, h, c = real.shape
+            if c==3:
+                image = color_pic.filter(MyGaussianBlur(radius=5))
+                mat = np.atleast_2d(image)
+
+                if gray_pic.ndim == 2:
+                    gray_pic = np.expand_dims(gray_pic, 2)
+                    gray_pic = np.tile(gray_pic, [1, 1, 3])
+ 
+
+
+                for i in range(n_point):
+                    length = 0
+                    while length < min_length:
+                        ws, hs, wt, ht, length = gen_color_line(mat, dir,max_length,max_dif)
+                    gray_pic[ws:wt, hs:ht, :] = mat[ws:wt, hs:ht, :]
+
+                gray_pic = np.append(real, gray_pic, axis=1)
+                final_img = Image.fromarray(gray_pic)
+
+                im = final_img
+                w, h = im.size
+                hsize = int(h * wsize / float(w))
+                if hsize * 2 > wsize:  # crop to three
+                    im = im.resize((wsize, hsize))
+                    bounds1 = (0, 0, wsize, int(wsize / 2))
+                    cropImg1 = im.crop(bounds1)
+                    # cropImg1.show()
+                    cropImg1.save(os.path.join(out_dir, 'u' + filename))
+                    bounds2 = (0, hsize - int(wsize / 2), wsize, hsize)
+                    cropImg2 = im.crop(bounds2)
+                # cropImg.show()
+                    cropImg2.save(os.path.join(out_dir, 'd' + filename))
+                else:
+                    im = im.resize((wsize, (wsize // 2)))
+                    im.save(os.path.join(out_dir, 't' + filename))
+                count += 1
+                print('done!' + str(count))
+
+
+                # io.imsave(os.path.join(out_dir, filename), differencedIm2.astype(np.uint8))
+
+
+if __name__ == '__main__':
+    main()

.idea/misc.xml

@@ -0,0 +1 @@
+Put your orginal picture here!

.idea/modules.xml

@@ -0,0 +1,158 @@
+from PIL import Image, ImageEnhance, ImageFilter
+from pylab import *
+# import numpy as np
+from scipy.ndimage import filters
+# from skimage import io
+import glob, os
+
+in_dir = 'pic_org'
+out_dir = 'pic_sketch'
+if not os.path.exists(out_dir): os.mkdir(out_dir)
+
+
+class MyGaussianBlur(ImageFilter.Filter):
+    name = "GaussianBlur"
+
+    def __init__(self, radius=2, bounds=None):
+        self.radius = radius
+        self.bounds = bounds
+
+    def filter(self, image):
+        if self.bounds:
+            clips = image.crop(self.bounds).gaussian_blur(self.radius)
+            image.paste(clips, self.bounds)
+            return image
+        else:
+            return image.gaussian_blur(self.radius)
+
+
+def start(mat):
+    w, h, c = mat.shape
+    ws = int(w * random(1))
+    hs = int(h * random(1))
+    while (mat[ws, hs, 0] > 254) and (mat[ws, hs, 1] > 254) and (mat[ws, hs, 2] > 254):
+        ws = int(w * random(1))
+        hs = int(h * random(1))
+    return ws, hs
+
+
+def gen_color_line(mat, dir,max_length,max_dif):
+    w, h, c = mat.shape
+    ws = int(w * random(1))
+    hs = int(h * random(1))
+    while (mat[ws, hs, 0] > 254) and (mat[ws, hs, 1] > 254) and (mat[ws, hs, 2] > 254):
+        ws = int(w * random(1))
+        hs = int(h * random(1))
+    if dir == 1:
+        wt = ws
+        ht = hs
+        while (wt < w - 1) and (abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                        int(mat[wt + 1, ht, 1]) + int(mat[wt + 1, ht, 2]) + int(mat[wt + 1, ht, 0]))) < 80):
+            wt = wt + 1
+    if dir == 2:
+        wt = ws
+        ht = hs
+        while (ht < h - 1) and (abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                        int(mat[wt, ht + 1, 1]) + int(mat[wt, ht + 1, 2]) + int(mat[wt, ht + 1, 0]))) < 3):
+            ht = ht + 1
+    if dir == 3:
+        wt = ws
+        ht = hs
+        length = 0
+        while (length < max_length) and (wt < w-1) and (ht < h-1) and (
+            abs(int(mat[wt, ht, 1]) + int(mat[wt, ht, 2]) + int(mat[wt, ht, 0]) - (
+                            int(mat[wt + 1, ht + 1, 1]) + int(mat[wt + 1, ht + 1, 2]) + int(
+                        mat[wt + 1, ht + 1, 0]))) < max_dif):
+            ht += 1
+            wt += 1
+            length = abs(wt - ws) + abs(ht - hs)
+    return ws, hs, wt, ht, length
+
+
+def main():
+    
+    count = 0
+    #parameter
+    wsize = 1024  # double the resolution
+    Gamma = 0.97
+    Phi = 200
+    Epsilon = 0.1
+    k = 2
+    Sigma = 1.5
+    max_length=20
+    min_length=10
+    max_dif=30
+    n_point=50
+    dir = 3
+
+    input_paths = glob.glob(in_dir+ '/*.jpg')	
+    input_paths+=(glob.glob(in_dir+ '/*.jpeg'))
+    input_paths+=(glob.glob(in_dir+ '/*.png'))
+    for files1 in input_paths:
+        filepath, filename = os.path.split(files1)
+
+        im = Image.open(files1).convert('L')
+        im = array(ImageEnhance.Sharpness(im).enhance(3.0))
+        im2 = filters.gaussian_filter(im, Sigma)
+        im3 = filters.gaussian_filter(im, Sigma * k)
+        differencedIm2 = im2 - (Gamma * im3)
+        (x, y) = shape(im2)
+        for i in range(x):
+            for j in range(y):
+                if differencedIm2[i, j] < Epsilon:
+                    differencedIm2[i, j] = 1
+                else:
+                    differencedIm2[i, j] = 250 + tanh(Phi * (differencedIm2[i, j]))
+
+
+        gray_pic = differencedIm2.astype(np.uint8)
+        color_pic = Image.open(files1)
+        real = np.atleast_2d(color_pic)
+        
+        
+        if real.ndim == 3:
+            w, h, c = real.shape
+            if c==3:
+                image = color_pic.filter(MyGaussianBlur(radius=5))
+                mat = np.atleast_2d(image)
+
+                if gray_pic.ndim == 2:
+                    gray_pic = np.expand_dims(gray_pic, 2)
+                    gray_pic = np.tile(gray_pic, [1, 1, 3])
+ 
+
+
+         #       for i in range(n_point):
+          #          length = 0
+           #         while length < min_length:
+            #            ws, hs, wt, ht, length = gen_color_line(mat, dir,max_length,max_dif)
+             #       gray_pic[ws:wt, hs:ht, :] = mat[ws:wt, hs:ht, :]
+
+                gray_pic = np.append(real, gray_pic, axis=1)
+                final_img = Image.fromarray(gray_pic)
+
+                im = final_img
+                w, h = im.size
+                hsize = int(h * wsize / float(w))
+                if hsize * 2 > wsize:  # crop to three
+                    im = im.resize((wsize, hsize))
+                    bounds1 = (0, 0, wsize, int(wsize / 2))
+                    cropImg1 = im.crop(bounds1)
+                    # cropImg1.show()
+                    cropImg1.save(os.path.join(out_dir, 'u' + filename))
+                    bounds2 = (0, hsize - int(wsize / 2), wsize, hsize)
+                    cropImg2 = im.crop(bounds2)
+                # cropImg.show()
+                    cropImg2.save(os.path.join(out_dir, 'd' + filename))
+                else:
+                    im = im.resize((wsize, (wsize // 2)))
+                    im.save(os.path.join(out_dir, 't' + filename))
+                count += 1
+                print('done!' + str(count))
+
+
+                # io.imsave(os.path.join(out_dir, filename), differencedIm2.astype(np.uint8))
+
+
+if __name__ == '__main__':
+    main()