app.py

import os
import gradio as gr
import requests
import json
from PIL import Image
import cv2
import numpy as np

# Your existing CSS remains unchanged
# I'll keep your helper functions (convert_fun, get_attributes, check_liveness) mostly the same
# but add better error handling

def get_attributes(frame):
    if frame is None:
        return None, "No image provided"
    
    url = "https://recognito.p.rapidapi.com/api/analyze_face"
    try:
        # If frame is a numpy array from webcam, convert to bytes
        if isinstance(frame, np.ndarray):
            _, buffer = cv2.imencode('.jpg', frame)
            files = {'image': ('image.jpg', buffer.tobytes(), 'image/jpeg')}
        else:
            files = {'image': open(frame, 'rb')}
        
        headers = {"X-RapidAPI-Key": os.environ.get("API_KEY")}
        r = requests.post(url=url, files=files, headers=headers)
    except Exception as e:
        return None, f"Error processing image: {str(e)}"
    
    # Rest of your get_attributes function remains the same
    # ... (keeping your existing logic)
    return face_crop, one_line_attribute

def check_liveness(frame):
    if frame is None:
        return None, "No image provided", -200
    
    url = "https://recognito-faceliveness.p.rapidapi.com/api/check_liveness"
    try:
        if isinstance(frame, np.ndarray):
            _, buffer = cv2.imencode('.jpg', frame)
            files = {'image': ('image.jpg', buffer.tobytes(), 'image/jpeg')}
        else:
            files = {'image': open(frame, 'rb')}
        
        headers = {"X-RapidAPI-Key": os.environ.get("API_KEY")}
        r = requests.post(url=url, files=files, headers=headers)
    except Exception as e:
        return None, f"Error processing image: {str(e)}", -200
    
    # Rest of your check_liveness function remains the same
    # ... (keeping your existing logic)
    return face_crop, liveness_result, liveness_score

def analyze_face(frame):
    if frame is None:
        return [None, "No image provided", "Please provide an image or enable webcam"]
    
    face_crop_1, liveness_result, liveness_score = check_liveness(frame)
    face_crop_2, attribute = get_attributes(frame)
    
    face_crop = face_crop_1 if face_crop_1 is not None else face_crop_2
    return [face_crop, liveness_result, attribute]

# Modified interface with webcam support
with gr.Blocks(css=css) as demo:
    gr.Markdown(
        # Your existing header markdown
    )
    
    with gr.Tabs():
        with gr.Tab("Face Recognition"):
            # Keeping your existing Face Recognition tab unchanged
            # ...
            
        with gr.Tab("Face Liveness, Analysis"):
            with gr.Row():
                with gr.Column(scale=1):
                    # Modified input to include webcam
                    face_input = gr.Image(
                        label="Image (Upload or Webcam)",
                        sources=["upload", "webcam"],
                        type='filepath',  # Will be None for webcam frames
                        elem_classes="example-image",
                        streaming=True  # Enable continuous webcam streaming
                    )
                    gr.Examples(
                        ['examples/att_1.jpg', 'examples/att_2.jpg', 'examples/att_3.jpg'],
                        inputs=face_input
                    )

                with gr.Blocks():
                    with gr.Column(scale=1, elem_classes="block-background"):     
                        analyze_face_button = gr.Button("Analyze Face", variant="primary", size="lg")
                        with gr.Row(elem_classes="face-row"):
                            face_output = gr.Image(
                                value="icons/face.jpg",
                                label="Face",
                                scale=0,
                                elem_classes="face-image"
                            )
                        
                        liveness_result = gr.Markdown("")
                        attribute_result = gr.Markdown("")
                    
                    # Updated event handler for both upload and webcam
                    analyze_face_button.click(
                        analyze_face,
                        inputs=face_input,
                        outputs=[face_output, liveness_result, attribute_result]
                    )
                    # Add streaming event for webcam
                    face_input.stream(
                        analyze_face,
                        inputs=face_input,
                        outputs=[face_output, liveness_result, attribute_result],
                        _js="""(image) => {
                            if (image && image.data) return image;
                            return null;
                        }"""
                    )

    gr.HTML(
        # Your existing footer HTML
    )
    
demo.launch(server_name="0.0.0.0", server_port=7860, show_api=False)