import gradio as gr
import cv2
import dlib
import numpy as np
from skimage import feature

# Initialize your AntiSpoofingSystem class as previously defined
class AntiSpoofingSystem:
    def __init__(self):
        self.detector = dlib.get_frontal_face_detector()
        self.predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
        self.EAR_THRESHOLD = 0.25

    def calculate_ear(self, eye):
        A = np.linalg.norm(eye[1] - eye[5])
        B = np.linalg.norm(eye[2] - eye[4])
        C = np.linalg.norm(eye[0] - eye[3])
        return (A + B) / (2.0 * C)

    def analyze_texture(self, face_region):
        gray_face = cv2.cvtColor(face_region, cv2.COLOR_BGR2GRAY)
        lbp = feature.local_binary_pattern(gray_face, P=8, R=1, method="uniform")
        lbp_hist, _ = np.histogram(lbp.ravel(), bins=np.arange(0, 58), range=(0, 58))
        lbp_hist = lbp_hist.astype("float")
        lbp_hist /= (lbp_hist.sum() + 1e-5)
        return np.sum(lbp_hist[:10]) > 0.3

    def process_image(self, image):
        # Convert the image to grayscale and detect faces
        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
        faces = self.detector(gray)

        # If no face is detected, return a message
        if len(faces) == 0:
            return "No face detected. Please try again."

        # Process the first detected face
        face = faces[0]
        landmarks = self.predictor(gray, face)
        leftEye = np.array([(landmarks.part(n).x, landmarks.part(n).y) for n in range(36, 42)])
        rightEye = np.array([(landmarks.part(n).x, landmarks.part(n).y) for n in range(42, 48)])
        
        ear_left = self.calculate_ear(leftEye)
        ear_right = self.calculate_ear(rightEye)

        # Determine if a blink is detected
        blink_detected = (ear_left < self.EAR_THRESHOLD and ear_right < self.EAR_THRESHOLD)
        return "Blink detected!" if blink_detected else "No blink detected."

# Define the Gradio interface
anti_spoofing_system = AntiSpoofingSystem()

def detect_blink(image):
    result = anti_spoofing_system.process_image(image)
    return result

iface = gr.Interface(
    fn=detect_blink,
    inputs=gr.Image(shape=(720, 1280)),
    outputs="text",
    title="Anti-Spoofing Detection System",
    description="Upload an image with a face to detect if a blink is detected."
)

# Launch the Gradio interface
iface.launch()