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import os |
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import cv2 |
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import uuid |
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import gradio as gr |
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import numpy as np |
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import neovision |
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import random |
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MARKDOWN = """ |
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# Welcome to VisionB 🧠 + 📸 |
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Meet VisionB, your Visual Agent that combines the power of advanced GPT models with real-time visual inputs. Engage in interactive dialogues, ask questions, and gain insights with the added context of images from your webcam. Experience a new dimension of interaction where vision and conversational AI meet. |
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""" |
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connector = neovision.OpanAIConnector() |
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def generate_liveness_challenge(image_details): |
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challenges = [] |
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if 'glasses' in image_details: |
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challenges.append("Please take off your glasses and hold them in your hand.") |
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if 'smiling' in image_details: |
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challenges.append("Please take another picture with a neutral expression.") |
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if not challenges: |
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challenges = [ |
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"Please hold up 5 fingers.", |
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"Use your hand to cover one of your eyes.", |
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"Make an OK sign with your hand and hold it up to your chin." |
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] |
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return random.choice(challenges) |
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def save_image_to_drive(image: np.ndarray) -> str: |
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image_filename = f"{uuid.uuid4()}.jpeg" |
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image_directory = "data" |
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os.makedirs(image_directory, exist_ok=True) |
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image_path = os.path.join(image_directory, image_filename) |
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cv2.imwrite(image_path, image) |
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return image_path |
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def respond(image: np.ndarray, prompt: str, chat_history=None): |
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if chat_history is None: |
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chat_history = [] |
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image = np.fliplr(image) |
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
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image_path = save_image_to_drive(image) |
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if 'verify' in prompt.lower(): |
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image_details = "A Person Wearing glasses" |
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challenge = generate_liveness_challenge(image_details) |
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response = f"For liveness verification, {challenge}" |
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else: |
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response = connector.simple_prompt(image=image, prompt=prompt) |
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chat_history.append(((image_path,), None)) |
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chat_history.append((prompt, response)) |
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return "", chat_history |
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with gr.Blocks() as demo: |
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gr.Markdown(MARKDOWN) |
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with gr.Row(): |
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webcam = gr.Image(sources=["webcam"], streaming=True) |
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with gr.Column(): |
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chatbot = gr.Chatbot(height=500) |
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message = gr.Textbox() |
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clear_button = gr.ClearButton([message, chatbot]) |
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message.submit(respond, [webcam, message, chatbot], [message, chatbot]) |
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demo.launch(debug=False, show_error=True) |