Update app.py

app.py

@@ -9,7 +9,71 @@ pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, model
 mp_drawing = mp.solutions.drawing_utils
 
 # Define a function to classify yoga poses
-def classify_pose(landmarks):
+def classifyPose(landmarks, output_image, display=False):
+    '''
+    This function classifies yoga poses depending upon the angles of various body joints.
+    Args:
+        landmarks: A list of detected landmarks of the person whose pose needs to be classified.
+        output_image: A image of the person with the detected pose landmarks drawn.
+        display: A boolean value that is if set to true the function displays the resultant image with the pose label
+        written on it and returns nothing.
+    Returns:
+        output_image: The image with the detected pose landmarks drawn and pose label written.
+        label: The classified pose label of the person in the output_image.
+
+    '''
+
+    # Initialize the label of the pose. It is not known at this stage.
+    label = 'Unknown Pose'
+
+    # Specify the color (Red) with which the label will be written on the image.
+    color = (0, 0, 255)
+
+    # Calculate the required angles.
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Get the angle between the left shoulder, elbow and wrist points.
+    left_elbow_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
+                                      landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value],
+                                      landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value])
+
+    # Get the angle between the right shoulder, elbow and wrist points.
+    right_elbow_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
+                                       landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value],
+                                       landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value])
+
+    # Get the angle between the left elbow, shoulder and hip points.
+    left_shoulder_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value],
+                                         landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
+                                         landmarks[mp_pose.PoseLandmark.LEFT_HIP.value])
+
+    # Get the angle between the right hip, shoulder and elbow points.
+    right_shoulder_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
+                                          landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
+                                          landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value])
+
+    # Get the angle between the left hip, knee and ankle points.
+    left_knee_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
+                                     landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value],
+                                     landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value])
+
+    # Get the angle between the right hip, knee and ankle points
+    right_knee_angle = calculateAngle(landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
+                                      landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value],
+                                      landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value])
+
+    #----------------------------------------------------------------------------------------------------------------
+    # Check for Five-Pointed Star Pose
+    if abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][1] - landmarks[mp_pose.PoseLandmark.LEFT_HIP.value][1]) < 100 and \
+       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][1] - landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value][1]) < 100 and \
+       abs(landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value][0] - landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value][0]) > 200 and \
+       abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][0] - landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][0]) > 200:
+        label = "Five-Pointed Star Pose"  
+        
+    # Check if it is the warrior II pose or the T pose.
+    # As for both of them, both arms should be straight and shoulders should be at the specific angle.
+    #----------------------------------------------------------------------------------------------------------------
+
     # Check if the both arms are straight.
     if left_elbow_angle > 165 and left_elbow_angle < 195 and right_elbow_angle > 165 and right_elbow_angle < 195:
 
@@ -61,8 +125,19 @@ def classify_pose(landmarks):
        abs(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value][1] - landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value][1]) < 50:
         label = "Upward Salute Pose"
 
-    # Add more classification rules here
-            return "Unknown Pose"
+   # Check for Hands Under Feet Pose
+    if landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][1] > landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value][1] and \
+       landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][1] > landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value][1] and \
+       abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][0] - landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value][0]) < 50 and \
+       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][0] - landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value][0]) < 50:
+        label = "Hands Under Feet Pose"      
+        
+       
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Check if the pose is classified successfully
+    if label != 'Unknown Pose':
+
 
 def detect_and_classify_pose(input_image):
     frame = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)