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| 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) |