Blue background

@@ -28,9 +28,9 @@ class DetectFace:
         # init face parts
         self.mouth = []
         self.right_eyebrow = []
-        self. left_eyebrow = []
+        self.left_eyebrow = []
         self.right_eye = []
-        self. left_eye = []
+        self.left_eye = []
         self.nose = []
         self.jaw = []
         self.cheek_img = [[],[]] # index 0 : left, 1 : right
@@ -107,22 +107,48 @@ class DetectFace:
         cv2.fillConvexPoly(mask, pts, 1)
         mask = mask.astype(np.bool)
 
+        print(mask)
+
+        # Mask For background
+        inversed_mask = np.logical_not(mask)
+        print(inversed_mask)
+
+
+        # Create a blank black image
+        blue = np.zeros_like(self.img)
+        # Fill image with blue color(set each pixel to blue)
+        blue[:] = [255, 0, 0]
+        # extract background by applying inversed_mask
+        print(inversed_mask.shape)
+        print(blue.shape)
+        print(type(self.img))
+        print(type(blue))
+        print(mask.shape)
+        print(self.img.shape)
+
+        # extract right eye by applying polygon mask
+        out2 = np.zeros_like(self.img)
+        out2[inversed_mask] = blue[inversed_mask]
+        cv2.imshow("out2", out2)
+        cv2.waitKey(0)
+
         # extract right eye by applying polygon mask
         out = np.zeros_like(self.img)
         out[mask] = self.img[mask]
-        '''
-        cv2.imshow("Image2", out)
+        #out = out[mask] + blue
+
+        cv2.imshow("out", out)
         cv2.waitKey(0)
-        '''
 
         # crop the image
         (x, y, w, h) = cv2.boundingRect(pts)
-        extracted_part = out[y:y + h, x:x + w]
-        '''
-        cv2.imshow("Image2", extracted_part)
+        crop1 = out[y:y + h, x:x + w]
+        crop2 = out2[y:y + h, x:x + w]
+        crop = cv2.add(crop1,crop2)
+        cv2.imshow("Image2", crop)
         cv2.waitKey(0)
-        '''
-        return extracted_part
+
+        return crop
 
 
     # return type = image

@@ -3,7 +3,7 @@ from detect_face import DetectFace
 from dominant_colors import DominantColors
 
 # Set paths
-image = "res/lees.jpg"
+image = "res/fall_0_0.png"
 predictor = "shape_predictor_68_face_landmarks.dat"
 
 # Create an DetectFace instance
@@ -11,32 +11,30 @@ df = DetectFace(predictor, image)
 
 # Try: Extract mouth part
 mouth = df.extract_face_part(df.mouth)
-cv2.imshow("Mouth", mouth)
-cv2.waitKey(0)
 
 # Try: Extract right eye part
 r_eye = df.extract_face_part(df.right_eye)
-cv2.imshow("Right eye", r_eye)
-cv2.waitKey(0)
 
 # Try: Extract left eye part
 l_eye = df.extract_face_part(df.left_eye)
-cv2.imshow("Left eye", l_eye)
-cv2.waitKey(0)
 
 # Try : Extract cheek part
-cv2.imshow("Left cheek", df.cheek_img[0])
-cv2.waitKey(0)
-cv2.imshow("Right cheek", df.cheek_img[1])
-cv2.waitKey(0)
+l_cheek = df.cheek_img[0]
+r_cheek = df.cheek_img[1]
 
 
 # Create an DominantColors instance on left cheek image
 clusters = 5
-dc = DominantColors(df.cheek_img[0], clusters)
-colors = dc.dominantColors()
-print(colors)
-dc.plotHistogram()
+lc_dc = DominantColors(l_cheek, clusters)
+lc_colors = lc_dc.dominantColors()
+print(lc_colors)
+lc_dc.plotHistogram()
+
+# Create an DominantColors instance on left cheek image
+rc_dc = DominantColors(r_cheek, clusters)
+rc_colors = rc_dc.dominantColors()
+print(rc_colors)
+rc_dc.plotHistogram()
 
 # Try : Dominant color on right_eye
 clusters = 6

+봄
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+3 세진
+4 윤터터
+5 하늘
+
+여름
+0 도형
+1 연우
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+3 쿠키
+4 한별
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+
+가을
+0 제나
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+

 from scipy.spatial import distance
 import copy
-# RGB based standard
+from get_std_from_xls import ListFromExcel
+
+converter = ListFromExcel('res/tone_color_standard.xlsx')
+# STANDARD(RGB based)
 # list[0] = spring, [1] = summer, [2] = fall, [3] = winter
 label = ['spring', 'summer', 'fall', 'winter']
-skin = [[197, 159, 140], [200, 164, 150], [195, 156, 138], [204, 168, 156]]
-pupil = [[157, 92, 18], [145, 112, 28], [134, 96, 3], [136, 101, 10]]
-hair = [[152, 103, 47], [95, 82, 81], [121, 87, 66], [85, 64, 67]]
+skin_rgb = converter.get_rgb(converter.skin)
+pupil_rgb = converter.get_rgb(converter.pupil)
+hair_rgb = converter.get_rgb(converter.hair)
 
 # 이성경(res/lees.jpg) dominant colors by order of histogram
 skin_lsg = [[222.5, 201.4, 188.9], [227.2, 209.5, 203.3]] # left cheek