Update app.py

app.py

@@ -9,9 +9,10 @@ from recommendations import check_pose_angle
 from landmarks import extract_landmarks
 from calc_angles import rangles
 
-
 def init_cam():
-    cam = cv2.VideoCapture(0)
+    cam = cv2.VideoCapture(0)  # Use 0 for default camera
+    if not cam.isOpened():
+        raise ValueError("Could not open camera.")
     cam.set(cv2.CAP_PROP_AUTOFOCUS, 0)
     cam.set(cv2.CAP_PROP_FOCUS, 360)
     cam.set(cv2.CAP_PROP_BRIGHTNESS, 130)
@@ -20,7 +21,6 @@ def init_cam():
     cam.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
     return cam
 
-
 def get_pose_name(index):
     names = {
         0: "Adho Mukha Svanasana",
@@ -28,8 +28,7 @@ def get_pose_name(index):
         2: "Utkata Konasana",
         3: "Vrikshasana",
     }
-    return str(names[index])
-
+    return str(names.get(index, "Unknown Pose"))
 
 def init_dicts():
     landmarks_points = {
@@ -43,26 +42,9 @@ def init_dicts():
         "left_heel": 29, "right_heel": 30,
         "left_foot_index": 31, "right_foot_index": 32,
     }
-    landmarks_points_array = {
-        "left_shoulder": [], "right_shoulder": [],
-        "left_elbow": [], "right_elbow": [],
-        "left_wrist": [], "right_wrist": [],
-        "left_hip": [], "right_hip": [],
-        "left_knee": [], "right_knee": [],
-        "left_ankle": [], "right_ankle": [],
-        "left_heel": [], "right_heel": [],
-        "left_foot_index": [], "right_foot_index": [],
-    }
-    col_names = []
-    for i in range(len(landmarks_points.keys())):
-        name = list(landmarks_points.keys())[i]
-        col_names.append(name + "_x")
-        col_names.append(name + "_y")
-        col_names.append(name + "_z")
-        col_names.append(name + "_v")
-    cols = col_names.copy()
-    return cols, landmarks_points_array
-
+    landmarks_points_array = {key: [] for key in landmarks_points.keys()}
+    col_names = [f"{name}_{axis}" for name in landmarks_points.keys() for axis in ["x", "y", "z", "v"]]
+    return col_names, landmarks_points_array
 
 def cv2_put_text(image, message):
     cv2.putText(
@@ -76,44 +58,39 @@ def cv2_put_text(image, message):
         cv2.LINE_AA
     )
 
-
 def destroy(cam):
-    cv2.destroyAllWindows()
     cam.release()
-
+    cv2.destroyAllWindows()
 
 if __name__ == "__main__":
-    cam = init_cam()
-    model = pk.load(open("./models/4_poses.model", "rb"))
-    cols, landmarks_points_array = init_dicts()
-    angles_df = pd.read_csv("./csv_files/4_angles_poses_angles.csv")
-    mp_drawing = mp.solutions.drawing_utils
-    mp_pose = mp.solutions.pose
-
-    tts_last_exec = time() + 5
-
-    while True:
-        result, image = cam.read()
-        flipped = cv2.flip(image, 1)
-        resized_image = cv2.resize(
-            flipped,
-            (640, 360),
-            interpolation=cv2.INTER_AREA
-        )
-
-        key = cv2.waitKey(1)
-        if key == ord("q"):
-            destroy(cam)
-            break
-
-        if result:
+    try:
+        cam = init_cam()
+        model = pk.load(open("./models/4_poses.model", "rb"))
+        cols, landmarks_points_array = init_dicts()
+        angles_df = pd.read_csv("./csv_files/4_angles_poses_angles.csv")
+        mp_drawing = mp.solutions.drawing_utils
+        mp_pose = mp.solutions.pose
+
+        while True:
+            result, image = cam.read()
+            if not result:
+                print("Failed to grab frame.")
+                break
+
+            flipped = cv2.flip(image, 1)
+            resized_image = cv2.resize(
+                flipped,
+                (640, 360),
+                interpolation=cv2.INTER_AREA
+            )
+
             err, df, landmarks = extract_landmarks(
                 resized_image,
                 mp_pose,
                 cols
             )
 
-            if err == False:
+            if not err:
                 prediction = model.predict(df)
                 probabilities = model.predict_proba(df)
 
@@ -133,13 +110,10 @@ if __name__ == "__main__":
                     suggestions = check_pose_angle(
                         prediction[0], angles, angles_df)
 
-                    if time() > tts_last_exec:
-                        # Display suggestions on screen
-                        cv2_put_text(
-                            flipped,
-                            suggestions[0]
-                        )
-                        tts_last_exec = time() + 5
+                    cv2_put_text(
+                        flipped,
+                        suggestions[0]
+                    )
 
                 else:
                     cv2_put_text(
@@ -147,3 +121,7 @@ if __name__ == "__main__":
                         "No Pose Detected"
                     )
             cv2.imshow("Frame", flipped)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
+    finally:
+        destroy(cam)