Update app.py

app.py

@@ -1,136 +1,154 @@
-import gradio as gr
-import cv2
-import mediapipe as mp
-import numpy as np
-
-# Initialize mediapipe pose class
-mp_pose = mp.solutions.pose
-pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, model_complexity=1)
-mp_drawing = mp.solutions.drawing_utils
-
-# Function to calculate the angle between three points
-def calculate_angle(a, b, c):
-    a = np.array([a.x, a.y])  # First point
-    b = np.array([b.x, b.y])  # Mid point
-    c = np.array([c.x, c.y])  # End point
-    
-    radians = np.arctan2(c[1] - b[1], c[0] - b[0]) - np.arctan2(a[1] - b[1], a[0] - b[0])
-    angle = np.abs(radians * 180.0 / np.pi)
-    
-    if angle > 180.0:
-        angle = 360 - angle
-        
-    return angle
-
-# Define a function to classify yoga poses
-def classify_pose(landmarks, output_image, display=False):
+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
-    left_elbow_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value])
-
-    right_elbow_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value])
-
-    left_shoulder_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_HIP.value])
-
-    right_shoulder_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value])
-
-    left_knee_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.LEFT_HIP.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value],
-        landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value])
-
-    right_knee_angle = calculate_angle(
-        landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value],
-        landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value])
+    # 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].y - landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].y) < 0.1 and \
-       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y - landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value].y) < 0.1 and \
-       abs(landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x - landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value].x) > 0.2 and \
-       abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x - landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x) > 0.2:
-        label = "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:
+
+        # Check if shoulders are at the required angle.
+        if left_shoulder_angle > 80 and left_shoulder_angle < 110 and right_shoulder_angle > 80 and right_shoulder_angle < 110:
+
+    # Check if it is the warrior II pose.
+    #----------------------------------------------------------------------------------------------------------------
+
+            # Check if one leg is straight.
+            if left_knee_angle > 165 and left_knee_angle < 195 or right_knee_angle > 165 and right_knee_angle < 195:
+
+                # Check if the other leg is bended at the required angle.
+                if left_knee_angle > 90 and left_knee_angle < 120 or right_knee_angle > 90 and right_knee_angle < 120:
+
+                    # Specify the label of the pose that is Warrior II pose.
+                    label = 'Warrior II Pose'
+
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Check if it is the T pose.
+    #----------------------------------------------------------------------------------------------------------------
+
+            # Check if both legs are straight
+            if left_knee_angle > 160 and left_knee_angle < 195 and right_knee_angle > 160 and right_knee_angle < 195:
+
+                # Specify the label of the pose that is tree pose.
+                label = 'T Pose'
     
-    # Check for Warrior II pose
-    if 165 < left_elbow_angle < 195 and 165 < right_elbow_angle < 195 and \
-       80 < left_shoulder_angle < 110 and 80 < right_shoulder_angle < 110:
-        if (165 < left_knee_angle < 195 or 165 < right_knee_angle < 195) and \
-           (90 < left_knee_angle < 120 or 90 < right_knee_angle < 120):
-            label = 'Warrior II Pose'
-
-    # Check for T pose
-    if 165 < left_elbow_angle < 195 and 165 < right_elbow_angle < 195 and \
-       80 < left_shoulder_angle < 110 and 80 < right_shoulder_angle < 110 and \
-       160 < left_knee_angle < 195 and 160 < right_knee_angle < 195:
-        label = 'T Pose'
-
-    # Check for Tree Pose
-    if (165 < left_knee_angle < 195 or 165 < right_knee_angle < 195) and \
-       (315 < left_knee_angle < 335 or 25 < right_knee_angle < 45):
-        label = 'Tree Pose'
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Check if it is the tree pose.
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Check if one leg is straight
+    if left_knee_angle > 165 and left_knee_angle < 195 or right_knee_angle > 165 and right_knee_angle < 195:
+
+        # Check if the other leg is bended at the required angle.
+        if left_knee_angle > 315 and left_knee_angle < 335 or right_knee_angle > 25 and right_knee_angle < 45:
+
+            # Specify the label of the pose that is tree pose.
+            label = 'Tree Pose'
     
     # Check for Upward Salute Pose
-    if abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x - landmarks[mp_pose.PoseLandmark.LEFT_HIP.value].x) < 0.1 and \
-       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x - landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value].x) < 0.1 and \
-       landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y < landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y and \
-       landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y < landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].y and \
-       abs(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y - landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value].y) < 0.05:
+    if abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][0] - landmarks[mp_pose.PoseLandmark.LEFT_HIP.value][0]) < 100 and \
+       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][0] - landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value][0]) < 100 and \
+       landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value][1] < landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value][1] and \
+       landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value][1] < landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value][1] and \
+       abs(landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value][1] - landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value][1]) < 50:
         label = "Upward Salute Pose"
 
-    # Check for Hands Under Feet Pose
-    if landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y > landmarks[mp_pose.PoseLandmark.LEFT_KNEE.value].y and \
-       landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y > landmarks[mp_pose.PoseLandmark.RIGHT_KNEE.value].y and \
-       abs(landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x - landmarks[mp_pose.PoseLandmark.LEFT_ANKLE.value].x) < 0.05 and \
-       abs(landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x - landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE.value].x) < 0.05:
-        label = "Hands Under Feet 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 for Plank Pose
+    #----------------------------------------------------------------------------------------------------------------
     # The body should be in a straight line from head to heels, 
     # so the shoulder and hip angles should be close to 180 degrees
     if left_shoulder_angle > 160 and left_shoulder_angle < 200 and \
        right_shoulder_angle > 160 and right_shoulder_angle < 200 and \
        left_knee_angle > 160 and left_knee_angle < 200 and \
        right_knee_angle > 160 and right_knee_angle < 200:
-        label = "Plank Pose"
-    
-    # Update the color to green if pose is classified
+        label = "Plank Pose"   
+    #----------------------------------------------------------------------------------------------------------------
+
+    # Check if the pose is classified successfully
     if label != 'Unknown Pose':
+
+        # Update the color (to green) with which the label will be written on the image.
         color = (0, 255, 0)
-    
-    # Write the label on the output image
-    cv2.putText(output_image, label, (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, color, 2)
-
-    return output_image, label
-
-def detect_and_classify_pose(input_image):
-    input_image = cv2.cvtColor(input_image, cv2.COLOR_BGR2RGB)
-    results = pose.process(input_image)
-    pose_classification = "No pose detected"
-    if results.pose_landmarks:
-        mp_drawing.draw_landmarks(input_image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
-        input_image, pose_classification = classify_pose(results.pose_landmarks.landmark, input_image)
-    return input_image, pose_classification
-
-iface = gr.Interface(
-    fn=detect_and_classify_pose,
-    inputs="image",
-    outputs=["image", "text"],
-    title="Live Yoga Pose Detection and Classification",
-    description="This app detects and classifies yoga poses from the live camera feed using MediaPipe.",
-)
-
-iface.launch()
+
+    # Write the label on the output image.
+    cv2.putText(output_image, label, (10, 30),cv2.FONT_HERSHEY_PLAIN, 2, color, 2)
+
+    # Check if the resultant image is specified to be displayed.
+    if display:
+
+        # Display the resultant image.
+        plt.figure(figsize=[10,10])
+        plt.imshow(output_image[:,:,::-1]);plt.title("Output Image");plt.axis('off');
+
+    else:
+
+        # Return the output image and the classified label.
+        return output_image, label