open eyes detector

app.py

@@ -23,6 +23,8 @@ def isEyeOpen(image):
     hist = cv2.calcHist([image], [0], None, [256], [0, 256])
     colors = np.where(hist > 10)
 
+    return np.mean(colors)
+
     if np.mean(colors) < 25:
         return True
     else:
@@ -38,7 +40,9 @@ def findIris(input_img1, input_img2, input_img3, input_img4, input_img5):
     with mp_face_mesh.FaceMesh(max_num_faces=1, refine_landmarks=True,
                                static_image_mode=True,
                                min_detection_confidence=0.45) as face_mesh:
-        for image in images:
+        #for image in images:
+        for id, image in enumerate(images):
+
             if image is None:
                 continue
 
@@ -77,9 +81,6 @@ def findIris(input_img1, input_img2, input_img3, input_img4, input_img5):
                     rightIris_top = (int(right_iris[1][0]), int(right_iris[1][1]))
                     rightIris_bottom = (int(right_iris[3][0]), int(right_iris[3][1]))
 
-
-
-
                     sizeIncrease = 0
                     leftEye = annotated_image[leftIris_top[1] - sizeIncrease : leftIris_bottom[1] + sizeIncrease,
                                              leftIris_leftside[0] - sizeIncrease : leftIris_rightside[0] + sizeIncrease]
@@ -89,24 +90,33 @@ def findIris(input_img1, input_img2, input_img3, input_img4, input_img5):
                               rightIris_leftside[0] - sizeIncrease: rightIris_rightside[0] + sizeIncrease]
                     rightEyeOpen = isEyeOpen(rightEye)
 
+                    cv2.putText(annotated_image, "Left " + str(int(leftEyeOpen)),
+                                (rightIris_leftside[0] - 20, leftIris_top[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
+                                1, (255, 255, 0), 1, cv2.LINE_AA)
+                    '''
                     if leftEyeOpen:
-                        cv2.putText(annotated_image, "Left Open",
+                        cv2.putText(annotated_image, "Left Open " + str(leftEyeOpen),
                                     (rightIris_leftside[0] - 20, leftIris_top[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
                                     1, (255, 255, 0), 1, cv2.LINE_AA)
                     else:
-                        cv2.putText(annotated_image, "Left Closed",
+                        cv2.putText(annotated_image, "Left Closed " + str(leftEyeOpen),
                                     (rightIris_leftside[0] - 20, leftIris_top[1] - 10), cv2.FONT_HERSHEY_SIMPLEX,
                                     1, (255, 255, 0), 1, cv2.LINE_AA)
-
+                    '''
+                    cv2.putText(annotated_image, "Right " + str(int(rightEyeOpen)),
+                                (rightIris_leftside[0] - 20, rightIris_top[1] + 50), cv2.FONT_HERSHEY_SIMPLEX,
+                                1, (255, 255, 0), 1, cv2.LINE_AA)
+                    '''
                     if rightEyeOpen:
-                        cv2.putText(annotated_image, "Right Open",
+                        cv2.putText(annotated_image, "Right Open " + str(rightEyeOpen),
                                     (rightIris_leftside[0] - 20, rightIris_top[1] + 50), cv2.FONT_HERSHEY_SIMPLEX,
                                     1, (255, 255, 0), 1, cv2.LINE_AA)
                     else:
-                        cv2.putText(annotated_image, "Right Closed",
+                        cv2.putText(annotated_image, "Right Closed " + str(rightEyeOpen),
                                     (rightIris_leftside[0] - 20, rightIris_top[1] + 50), cv2.FONT_HERSHEY_SIMPLEX,
                                     1, (255, 255, 0), 1, cv2.LINE_AA)
                     #leftEye = cv2.cvtColor(leftEye, cv2.COLOR_BGR2GRAY)
+                    '''
 
                     '''
                     cv2.circle(annotated_image,
@@ -147,8 +157,50 @@ def findIris(input_img1, input_img2, input_img3, input_img4, input_img5):
                     right = rightIris_rightside[0] + 150
                     up = leftIris_top[1] - 50
                     down = leftIris_bottom[1] + 50
+
+                    boundryIncrease = 10
+                    print("leftside = ",  leftIris_leftside[0])
+                    print("rightside =",  leftIris_rightside[0])
+                    #print("left = ", left)
+                    #print("right = ", right)
+
+                    '''
+                    if (id == 1): # Looking Left so we want the right limbus
+                        print("Id == 1")
+                        annotated_image = annotated_image[
+                                          leftIris_top[1]  : leftIris_bottom[1],
+                                          leftIris_rightside[0] - boundryIncrease : leftIris_rightside[0] + boundryIncrease
+                                          ]
+                        annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2GRAY)
+                        #annotated_image = cv2.GaussianBlur(annotated_image, (3, 3), sigmaX=0, sigmaY=0)
+                        annotated_image = cv2.Canny(annotated_image, 50, 125)
+                        #annotated_image = cv2.Sobel(src=annotated_image, ddepth=cv2.CV_64F, dx=0, dy=1,
+                        #                   ksize=5)  # Sobel Edge Detection on the Y axis
+
+                        contours = cv2.findContours(image, cv2.RETR_LIST, cv2.RETR_EXTERNAL)
+                        contours = sorted(contours, key=cv2.contourArea, reverse=True)
+                        for i in range(len(contours)):
+                            contour = contours[i]
+                            random.seed(i)
+                            color = (255 * random.random(), 255 * random.random(), 255 * random.random())
+                            cv2.drawContours(img, [contour], -1, color, 3)
+
+
+
+                    elif (id == 2): # Looking Right so we want the left limbus
+                        annotated_image = annotated_image[
+                                          leftIris_top[1]: leftIris_bottom[1],
+                                          leftIris_leftside[0] - boundryIncrease: leftIris_leftside[0] + boundryIncrease
+                                          ]
+                        annotated_image = cv2.cvtColor(annotated_image, cv2.COLOR_BGR2GRAY)
+                        # annotated_image = cv2.GaussianBlur(annotated_image, (3, 3), sigmaX=0, sigmaY=0)
+                        annotated_image = cv2.Canny(annotated_image, 50, 125)
+                    else:
+                    '''
                     annotated_image = annotated_image[up:down, left:right]
 
+
+
                     x1 = (leftIris_leftside[0] - nose[0] + leftIris_rightside[0] - nose[0]) / 2
                     y1 = (leftIris_top[1] - nose[1] + leftIris_bottom[1] - nose[1]) / 2
                     x2 = (rightIris_leftside[0] - nose[0] + rightIris_rightside[0] - nose[0]) / 2