Update utils.py

utils.py

@@ -9,16 +9,14 @@ incorrect = cv2.imread('wrong.png')
 incorrect = cv2.cvtColor(incorrect, cv2.COLOR_BGR2RGB)
 
 def draw_rounded_rect(img, rect_start, rect_end, corner_width, box_color):
-        """
-            This function draws a rectangle with rounded corners on an image.
-          Args:
-              img: The image to draw on.
-              rect_start: The top-left corner of the rectangle as a tuple (x1, y1).
-              rect_end: The bottom-right corner of the rectangle as a tuple (x2, y2).
-              corner_width: The width of the rounded corners.
-              box_color: The color of the rectangle in BGR format.
-          """
-
+        
+        #    This function draws a rectangle with rounded corners on an image.
+        # Args:
+              #img: The image to draw on.
+              #rect_start: The top-left corner of the rectangle as a tuple (x1, y1).
+              #rect_end: The bottom-right corner of the rectangle as a tuple (x2, y2).
+              #corner_width: The width of the rounded corners.
+              #box_color: The color of the rectangle in BGR format.
     
     x1, y1 = rect_start
     x2, y2 = rect_end
@@ -47,16 +45,16 @@ def draw_rounded_rect(img, rect_start, rect_end, corner_width, box_color):
     return img
 
 def draw_dotted_line(frame, lm_coord, start, end, line_color):
-        """
-          This function draws a dotted line on a frame based on landmark coordinates.
+        
+          #This function draws a dotted line on a frame based on landmark coordinates.
     
-        Args:
-          frame: The image to draw on.
-          lm_coord: The landmark coordinates as a NumPy array.
-          start: The index of the starting landmark in the lm_coord array.
-          end: The index of the ending landmark in the lm_coord array.
-          line_color: The color of the line in BGR format.
-        """
+        #Args:
+          #frame: The image to draw on.
+          #lm_coord: The landmark coordinates as a NumPy array.
+          #start: The index of the starting landmark in the lm_coord array.
+          #end: The index of the ending landmark in the lm_coord array.
+          #line_color: The color of the line in BGR format.
+        
     
     pix_step = 0
 
@@ -80,25 +78,25 @@ def draw_text(
     overlay_image = False,
     overlay_type = None
 ):
-      """
-  This function draws text with a customizable background box on an image.
-
-  Args:
-      img: The image to draw on.
-      msg: The message to display as a string.
-      width: The thickness of the background box border (default: 7).
-      font: The font style for the text (default: cv2.FONT_HERSHEY_SIMPLEX).
-      pos: The top-left corner coordinates of the text box (default: (0, 0)).
-      font_scale: The scaling factor for the font size (default: 1).
-      font_thickness: The thickness of the text (default: 2).
-      text_color: The color of the text in BGR format (default: green - (0, 255, 0)).
-      text_color_bg: The color of the background box in BGR format (default: black - (0, 0, 0)).
-      box_offset: The offset for the background box relative to the text (default: (20, 10)).
-      overlay_image: Flag to display an overlay image inside the box (default: False).
-      overlay_type: Type of overlay image ("correct" or "incorrect") - used when overlay_image is True.
-  Returns:
-      The size of the drawn text (width, height) as a NumPy array.
-  """
+
+  #This function draws text with a customizable background box on an image.
+
+  #Args:
+      #img: The image to draw on.
+      #msg: The message to display as a string.
+      #width: The thickness of the background box border (default: 7).
+      #font: The font style for the text (default: cv2.FONT_HERSHEY_SIMPLEX).
+      #pos: The top-left corner coordinates of the text box (default: (0, 0)).
+      #font_scale: The scaling factor for the font size (default: 1).
+      #font_thickness: The thickness of the text (default: 2).
+      #text_color: The color of the text in BGR format (default: green - (0, 255, 0)).
+      #text_color_bg: The color of the background box in BGR format (default: black - (0, 0, 0)).
+      #box_offset: The offset for the background box relative to the text (default: (20, 10)).
+      #overlay_image: Flag to display an overlay image inside the box (default: False).
+      #overlay_type: Type of overlay image ("correct" or "incorrect") - used when overlay_image is True.
+  #Returns:
+      #The size of the drawn text (width, height) as a NumPy array.
+
 
     offset = box_offset
     x, y = pos
@@ -150,17 +148,17 @@ def draw_text(
     return text_size
 
 def find_angle(p1, p2, ref_pt = np.array([0,0])):
-  """
-  This function calculates the angle between two points relative to a reference point.
 
-  Args:
-      p1: The first point coordinates as a NumPy array (x, y).
-      p2: The second point coordinates as a NumPy array (x, y).
-      ref_pt: The reference point coordinates as a NumPy array (default: [0, 0]).
+  #This function calculates the angle between two points relative to a reference point.
+
+  #Args:
+      #p1: The first point coordinates as a NumPy array (x, y).
+      #p2: The second point coordinates as a NumPy array (x, y).
+      #ref_pt: The reference point coordinates as a NumPy array (default: [0, 0]).
+
+  #Returns:
+      #The angle between the two points in degrees (int).
 
-  Returns:
-      The angle between the two points in degrees (int).
-  """
     # Subtract the reference point from both points for normalization
     p1_ref = p1 - ref_pt
     p2_ref = p2 - ref_pt
@@ -176,18 +174,18 @@ def find_angle(p1, p2, ref_pt = np.array([0,0])):
     return int(degree)
 
 def get_landmark_array(pose_landmark, key, frame_width, frame_height):
-  """
-  This function extracts the normalized image coordinates for a landmark.
 
-  Args:
-      pose_landmark: A MediaPipe pose landmark object.
-      key: The key name of the landmark to extract (e.g., 'nose', 'shoulder.x').
-      frame_width: The width of the image frame.
-      frame_height: The height of the image frame.
+  #This function extracts the normalized image coordinates for a landmark.
+
+  #Args:
+      #pose_landmark: A MediaPipe pose landmark object.
+      #key: The key name of the landmark to extract (e.g., 'nose', 'shoulder.x').
+      #frame_width: The width of the image frame.
+      #frame_height: The height of the image frame.
+
+  #Returns:
+      #A NumPy array containing the normalized x and y coordinates of the landmark.
 
-  Returns:
-      A NumPy array containing the normalized x and y coordinates of the landmark.
-  """
 
     denorm_x = int(pose_landmark[key].x * frame_width)
     denorm_y = int(pose_landmark[key].y * frame_height)
@@ -195,20 +193,18 @@ def get_landmark_array(pose_landmark, key, frame_width, frame_height):
     return np.array([denorm_x, denorm_y])
 
 def get_landmark_features(kp_results, dict_features, feature, frame_width, frame_height):
-  """
-  This function extracts landmark coordinates for various body parts based on a feature name.
 
-  Args:
-      kp_results: The MediaPipe pose landmark results object.
-      dict_features: A dictionary containing landmark key names for different body parts.
-      feature: The name of the body part feature to extract (e.g., 'nose', 'left', 'right').
-      frame_width: The width of the image frame.
-      frame_height: The height of the image frame.
+  #This function extracts landmark coordinates for various body parts based on a feature name.
 
-  Returns:
-      A list containing the landmark coordinates (as NumPy arrays) or raises an error if the feature is invalid.
-  """
+  #Args:
+      #kp_results: The MediaPipe pose landmark results object.
+      #dict_features: A dictionary containing landmark key names for different body parts.
+      #feature: The name of the body part feature to extract (e.g., 'nose', 'left', 'right').
+      #frame_width: The width of the image frame.
+      #frame_height: The height of the image frame.
 
+  #Returns:
+      #A list containing the landmark coordinates (as NumPy arrays) or raises an error if the feature is invalid.
     
     if feature == 'nose':
         return get_landmark_array(kp_results, dict_features[feature], frame_width, frame_height)