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Create app.py
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import os
import gradio as gr
import google.generativeai as genai
from PIL import Image
# Configure the Gemini API with environment variable
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
if not GOOGLE_API_KEY:
raise ValueError("GOOGLE_API_KEY environment variable not set. Please configure it in the Hugging Face Space settings.")
genai.configure(api_key=GOOGLE_API_KEY)
# Use Gemini 1.5 Flash model
model = genai.GenerativeModel('gemini-1.5-flash-latest')
def detect_deepfake(image):
if image is None:
return "Error: Please upload or capture an image."
# Resize image for consistency (optional, Gemini handles various sizes)
image = image.resize((224, 224))
prompt = """
You are an image analysis assistant tasked with detecting whether an image is a deepfake or real.
A deepfake is a synthetically generated or manipulated image, often of a human face, showing unnatural features like inconsistent lighting, unnatural textures, or blending artifacts.
A real image typically has natural lighting, consistent facial features, and no synthetic artifacts.
Classify the image as "Real" or "Deepfake" and provide a brief reason for your classification.
Return the response in this format:
Prediction: [Real / Deepfake]
Reason: [Brief explanation]
Examples:
Image Description: A face with consistent lighting, natural skin texture, and realistic eye movements.
Prediction: Real
Reason: The image shows natural lighting and facial features consistent with a real human photograph.
Image Description: A face with unnatural blending around the eyes, inconsistent lighting on the face, and slight pixelation.
Prediction: Deepfake
Reason: The unnatural blending and inconsistent lighting suggest synthetic manipulation typical of deepfakes.
Image Description: A face with smooth, overly perfect skin and slightly distorted facial proportions.
Prediction: Deepfake
Reason: The overly smooth skin and distorted proportions are indicative of AI-generated or manipulated images.
Image Description: A face with natural shadows, realistic hair texture, and consistent background lighting.
Prediction: Real
Reason: The natural shadows and realistic textures align with characteristics of a genuine photograph.
Classify the provided image.
Prediction:
Reason:
"""
try:
response = model.generate_content([prompt, image])
return response.text.strip()
except Exception as e:
return f"Error: {str(e)}\nTip: Ensure your API key is valid at https://aistudio.google.com/"
# Define Gradio interface
iface = gr.Interface(
fn=detect_deepfake,
inputs=gr.Image(type="pil", label="Upload or capture a face image", sources=["upload", "webcam"]),
outputs=gr.Textbox(label="Deepfake Detection Result"),
title="Deepfake Image Detector",
description="Upload or capture a face image to determine if it is Real or a Deepfake using the Gemini API. Set your GOOGLE_API_KEY in the Hugging Face Space settings."
)
# Launch the interface
if __name__ == "__main__":
iface.launch()