dominant colors

@@ -6,4 +6,4 @@ rgb = sRGBColor(222.5, 201.4, 188.9, is_upscaled=True)
 print(rgb)
 #lab로 변환. through_rgb_type=sRGBColor 로 넣어준다.(AdobeRGBColor클래스 사용 X)
 lab = convert_color(rgb, LabColor, through_rgb_type=sRGBColor)
-print(lab)
+print(type(lab.lab_l))

@@ -119,34 +119,28 @@ class DetectFace:
         # 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)
+        #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]
         #out = out[mask] + blue
 
-        cv2.imshow("out", out)
-        cv2.waitKey(0)
+        #cv2.imshow("out", out)
+        #cv2.waitKey(0)
 
         # crop the image
         (x, y, w, h) = cv2.boundingRect(pts)
         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)
+        #cv2.imshow("Image2", crop)
+        #cv2.waitKey(0)
 
         return crop
 

@@ -98,3 +98,4 @@ class DominantColors:
         plt.axis("off")
         plt.imshow(chart)
         plt.show()
+        print(" ")

@@ -83,6 +83,4 @@ class ListFromExcel:
                 temp.append([skin_list[i][s], hair_list[i][s], eye_list[i][s]])
             ret.append(temp)
             temp = []
-        for x in ret:
-            print(x)
         return ret

@@ -6,7 +6,7 @@ from getjson import GetJson
 import imutils
 from colormath.color_objects import LabColor, sRGBColor
 from colormath.color_conversions import convert_color
-
+'''
 # 이성경(res/lees.jpg) dominant colors by order of histogram
 # skin, hair, eye 순서
 lsk_rgb = [[222.5, 201.4, 188.9], [138.6, 98.4, 55.0], [159.8, 115.8, 61.7]]
@@ -59,29 +59,34 @@ r_cheek = df.cheek_img[1]
 clusters = 5
 lc_dc = DominantColors(l_cheek, clusters)
 lc_colors = lc_dc.dominantColors()
-print(lc_colors)
+print("left cheek")
 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)
+print("right cheek")
 rc_dc.plotHistogram()
 
-# Try : Dominant color on right_eye
+# Try : Dominant color on left_eye
 clusters = 6
+dc_le = DominantColors(l_eye, clusters)
+colors = dc_le.dominantColors()
+print("left eye")
+dc_le.plotHistogram()
+
+# Try : Dominant color on right_eye
 dc_re = DominantColors(r_eye, clusters)
 colors = dc_re.dominantColors()
-print(colors)
+print("right eye")
 dc_re.plotHistogram()
 
+
 # hair
 hair_img = "res/lees_hair.jpg"
 img = cv2.imread(hair_img)
 resized_img = imutils.resize(img, width = 100)
-clusters = 6
-dc_re = DominantColors(resized_img, clusters)
-colors = dc_re.dominantColors()
-print(colors)
-dc_re.plotHistogram()
-'''
+clusters = 5
+dc_hair = DominantColors(resized_img, clusters)
+colors = dc_hair.dominantColors()
+dc_hair.plotHistogram()