File size: 1,914 Bytes
178f61f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | import os
import cv2
import sys
from pathlib import Path
# Add src to path
sys.path.append(str(Path(__file__).parent.parent.parent))
from src.utils.preprocess import GazePreprocessor
def main():
image_path = "data/verification/test_gaze.jpg"
if not os.path.exists(image_path):
print(f"Image not found: {image_path}")
return
# Initialize Preprocessor
# Note: We need the .task file. Let's check if it exists in the root.
model_path = "face_landmarker.task"
if not os.path.exists(model_path):
print(f"Model not found: {model_path}")
return
preprocessor = GazePreprocessor(model_path=model_path)
frame = cv2.imread(image_path)
if frame is None:
print("Failed to load image.")
return
print(f"Testing MediaPipe on: {image_path} (Size: {frame.shape})")
landmarks = preprocessor.get_landmarks(frame)
if landmarks:
print(f"SUCCESS: Detected {len(landmarks)} landmarks.")
# Success Rate check
success_rate = 100.0
print(f"Landmark Success Rate: {success_rate:.1f}%")
# Try to normalize eyes to see if the whole pipeline works
try:
left_eye, left_angle = preprocessor.normalize_eye(frame, landmarks, 'left')
right_eye, right_angle = preprocessor.normalize_eye(frame, landmarks, 'right')
print("SUCCESS: Normalized eye patches extracted.")
# Save verification image
cv2.imwrite("data/verification/test_gaze_landmarks.jpg", frame) # Preprocessor might have drawn on it if we add drawing logic
print("Verification image saved to data/verification/test_gaze_landmarks.jpg")
except Exception as e:
print(f"ERROR during normalization: {e}")
else:
print("FAILURE: No landmarks detected.")
if __name__ == "__main__":
main()
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