pupilsense / image.py
vijul.shah
Input Video and Predictions as output video added
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import cv2
import numpy as np
# Load the original face image
face_image = cv2.imread("path_to_face_image.jpg")
# Suppose CAM_left and CAM_right are the CAM results for the eyes (each 32x64)
CAM_left = cv2.imread("path_to_CAM_left.jpg") # or generated by your model
CAM_right = cv2.imread("path_to_CAM_right.jpg") # or generated by your model
# Example bounding boxes for the left and right eye
left_eye_bbox = (x_left, y_left, width_left, height_left)
right_eye_bbox = (x_right, y_right, width_right, height_right)
# Resize CAM images if needed (they should be 32x64, but resize to match bbox size)
CAM_left_resized = cv2.resize(CAM_left, (width_left, height_left))
CAM_right_resized = cv2.resize(CAM_right, (width_right, height_right))
# Create a copy of the face image to overlay the CAM results
face_with_CAM = face_image.copy()
# Overlay left eye CAM
face_with_CAM[y_left : y_left + height_left, x_left : x_left + width_left] = CAM_left_resized
# Overlay right eye CAM
face_with_CAM[y_right : y_right + height_right, x_right : x_right + width_right] = CAM_right_resized
# Save or display the result
cv2.imwrite("face_with_CAM_overlay.jpg", face_with_CAM)
cv2.imshow("Face with CAM Overlay", face_with_CAM)
cv2.waitKey(0)
cv2.destroyAllWindows()