plot the seasons standards on Lab space

@@ -33,13 +33,13 @@ class DetectFace:
         self. left_eye = []
         self.nose = []
         self.jaw = []
-        self.cheek = [[],[]] # index 0 : left, 1 : right
+        self.cheek_img = [[],[]] # index 0 : left, 1 : right
 
         # detect the face parts and set the variables
-        self.detect_face_part()
-        self.cheek = self.detect_cheek()
-
+        self.detect_face_part() # mouth, right_eyebrow, ..., jaw : np.array
+        self.cheek_img = self.detect_cheek() # image
 
+    # return type : np.array
     def detect_face_part(self):
         # loop over the face detections
         # i : name
@@ -64,8 +64,8 @@ class DetectFace:
                 # specific face part
                 for (x, y) in shape[i:j]:
                     cv2.circle(clone, (x, y), 1, (0, 0, 255), -1)
-                #print(name)
-                #print(shape[i:j])
+                print(name)
+                print(shape[i:j])
 
                 face_parts[idx] = shape[i:j]
                 idx += 1
@@ -98,6 +98,7 @@ class DetectFace:
 
 
     # parameter example : self.right_eye
+    # return type : image
     def extract_face_part(self, part):
         pts = part
 
@@ -124,17 +125,17 @@ class DetectFace:
         return extracted_part
 
 
+    # return type = image
     def detect_cheek(self):
         cheek = [[],[]]
 
-        #rect is the face detected
+        # rect is the face detected
         shape = self.predictor(self.gray, self.rects[0])
         shape = face_utils.shape_to_np(shape)
 
-        left = self.img[shape[29][1]:shape[33][1],
-                        shape[4][0]:shape[48][0]] #left cheek
-        right = self.img[shape[29][1]:shape[33][1],
-                        shape[54][0]:shape[12][0]] #right cheek
+        # Cheeks are detected by relative position to the face landmarks
+        left = self.img[shape[29][1]:shape[33][1], shape[4][0]:shape[48][0]] #left cheek
+        right = self.img[shape[29][1]:shape[33][1], shape[54][0]:shape[12][0]] #right cheek
 
         cheek[0] = left
         cheek[1] = right

+import matplotlib.pyplot as plt
+from mpl_toolkits.mplot3d import Axes3D
+
+def plotStd(arr):
+    season_label = ['spring', 'summer', 'fall', 'winter']
+    season_color = ['green', 'blue', 'red', 'gray']
+    fig = plt.figure()
+    ax = Axes3D(fig)
+    for seasons in arr:
+        i = 0
+        for s in seasons:
+            ax.scatter(s[0], s[1], s[2], label = season_label[i], color = season_color[i])
+            i += 1
+    ax.set_xlabel('L value')
+    ax.set_ylabel('a value')
+    ax.set_zlabel('b value')
+#    plt.xlabel('L value')
+#    plt.ylabel('a value')
+#    plt.zlabel('b value')
+    plt.show()
+
+#[봄여름가을겨울]*5개의 기준
+skin_lab = [[[87.39, -2.2, 16.21],
+            [84.48, 0.75, 14.23],
+            [80.58, -0.1, 25.46],
+            [91.47, -0.7, 9.96]],
+           [[84.57, -0.21, 28.38],
+            [84.81, 6.59, 19.93],
+            [73.88, 2.55, 20.96],
+            [89.53, 0.74, 12.14]],
+           [[79.84, 11.02, 33.65],
+            [83.7, 5.53, 17.71],
+            [75.69, 4.55, 27.02],
+            [81.76, 14.12, 29.2]],
+           [[81.8, 6, 34.05],
+            [82.88, 10.99, 26.24],
+            [72.75, 3.2, 38.52],
+            [73.82, 8.42, 27.3]],
+		   [[83.4, 3.6575, 28.0725],
+            [83.9675, 5.965, 19.5275],
+            [75.725, 2.5575, 27.99],
+            [84.145, 5.6375, 19.65]]]
+
+plotStd(skin_lab)

@@ -12,7 +12,8 @@ skin_lsg = [[222.5, 201.4, 188.9], [227.2, 209.5, 203.3]] # left cheek
 pupil_lsg = [[159.8, 115.8, 61.7], [186.5, 156.1, 129.0],
              [126.0, 77.5, 42.8], [88.1, 41.1, 20.9]] # right eye
 
-
+skin_lab = [[87.39, -2.18, 16.21],[84.48, 0.75, 14.23],[80.58, -0.07, 25.46],[91.47, -0.73, 9.96]]
+skin_lsg_lab =  [[73.73, 19.20, 7.79],[70.94, 19.32, 8.28]] #left cheek
 '''
 for i in range(4):
     print(f'skin distance from {label[i]}')
@@ -25,6 +26,8 @@ for i in range(4):
     print('3 : ', distance.euclidean(pupil[i], pupil_lsg[2]))
     print('4 : ', distance.euclidean(pupil[i], pupil_lsg[3]))
 '''
+
+'''
 skin_dist = [[0,0,0,0], [0,0,0,0]]
 pupil_dist = [[0,0,0,0] for _ in range(4)]
 
@@ -56,6 +59,7 @@ print(sorted_ppdist[0])
 
 # 거리가 짧은 계절 순으로 출력
 # skin
+
 for i in range(2):
     print('skin - round ', i)
     for season in range(4):
@@ -66,3 +70,36 @@ for i in range(4):
     print('pupil - round ', i)
     for season in range(4):
         print(f'{season+1}위:', label[pupil_dist[i].index(sorted_ppdist[i][season])])
+'''
+
+
+## Lab 색상
+skin_dist_lab = [[0,0,0,0], [0,0,0,0]]
+pupil_dist_lab = [[0,0,0,0] for _ in range(4)]
+
+# i = seasons
+for i in range(4):
+    # skin
+    for j in range(2):
+    # j = 0 피부에서 가장 많은 색상과 각 계절과의 거리
+    # j = 1 피부에서 두번째로 많은 색상과 각 계절과의 거리
+        skin_dist_lab[j][i] = distance.euclidean(skin_lab[i], skin_lsg_lab[j])
+
+# 거리가 짧은 순으로 정렬
+# skin
+sorted_skdist_lab = copy.deepcopy(skin_dist_lab)
+
+for i in range(2):
+    sorted_skdist_lab[i].sort()
+
+print(skin_dist_lab[0])
+print(sorted_skdist_lab[0])
+
+# 거리가 짧은 계절 순으로 출력
+# skin
+
+for i in range(2):
+    print('skin - round ', i)
+    for season in range(4):
+        print(f'{season+1}위:', label[skin_dist_lab[i].index(sorted_skdist_lab[i][season])])
+print('\n')