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# utils.py
import numpy as np
import cv2
# Removed: import random, string, generate_gibberish
# Function to calculate Eye Aspect Ratio (EAR)
def calculate_ear(eye_landmarks, frame_shape):
"""
Calculates the Eye Aspect Ratio (EAR) for a given eye.
Args:
eye_landmarks: A list of 6 MediaPipe landmark objects for the eye.
Expected order: [p1, p2, p3, p4, p5, p6]
where p1, p4 are horizontal extremes, and p2, p3, p5, p6
are vertical extremes.
frame_shape: Tuple (height, width) of the frame.
Returns:
The calculated EAR value.
"""
if len(eye_landmarks) != 6:
# print("Warning: Expected 6 eye landmarks, but received", len(eye_landmarks)) # Optional warning
return 0.0 # Return 0 or handle error appropriately
# Convert MediaPipe landmarks to numpy array (pixel coordinates)
coords = np.array([(landmark.x * frame_shape[1], landmark.y * frame_shape[0])
for landmark in eye_landmarks])
# Calculate the Euclidean distances between the two sets of vertical eye landmarks
# p2-p6 and p3-p5
vertical_dist1 = np.linalg.norm(coords[1] - coords[5])
vertical_dist2 = np.linalg.norm(coords[2] - coords[4])
# Calculate the Euclidean distance between the horizontal eye landmark
# p1-p4
horizontal_dist = np.linalg.norm(coords[0] - coords[3])
# Calculate the EAR
# Avoid division by zero
if horizontal_dist == 0:
return 0.0
ear = (vertical_dist1 + vertical_dist2) / (2.0 * horizontal_dist)
return ear
def draw_landmarks(image, landmarks, connections=None, point_color=(0, 255, 0), connection_color=(255, 255, 255)):
"""
Draws landmarks and connections on the image.
Args:
image: The image (numpy array) to draw on.
landmarks: A list of MediaPipe landmark objects.
connections: A list of tuples representing landmark connections (e.g., [(0, 1), (1, 2)]).
point_color: Color for the landmarks (BGR tuple).
connection_color: Color for the connections (BGR tuple).
"""
if not landmarks:
return image
img_h, img_w, _ = image.shape
landmark_points = [(int(l.x * img_w), int(l.y * img_h)) for l in landmarks]
# Draw connections
if connections:
for connection in connections:
p1 = landmark_points[connection[0]]
p2 = landmark_points[connection[1]]
cv2.line(image, p1, p2, connection_color, 1)
# Draw points
for point in landmark_points:
cv2.circle(image, point, 2, point_color, -1)
return image |