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887f5f0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | import os
from google import genai
from google.genai import types
from PIL import Image
import json
class VLMAnalyzer:
def __init__(self):
self.api_key = os.getenv("GEMINI_API_KEY")
self.enabled = bool(self.api_key)
if self.enabled:
self.client = genai.Client(api_key=self.api_key)
else:
print("VLMAnalyzer disabled: GEMINI_API_KEY not found in .env")
def analyze_frame(self, image_array):
if not self.enabled:
return None
try:
pil_img = Image.fromarray(image_array).convert("RGB")
w, h = pil_img.width, pil_img.height
prompt = f"""
You are an expert deepfake detection AI.
Analyze the provided image for AI-generation artifacts, unnatural physics, logical inconsistencies, face swaps, or morphed hands/limbs.
Return a JSON strictly following this schema:
{{
"is_ai_generated": boolean,
"semantic_fake_score": float (0.0 to 1.0),
"reasoning": string (Detailed explanation of WHY it is fake based on physics, anatomy, or context. e.g. "The dog is walking on two feet". If real, explain why.),
"anomaly_regions": [
{{
"box": [x, y, w, h] (approximate integer pixel coordinates relative to image width {w} and height {h}),
"label": string (e.g., "morphed hand", "unnatural posture")
}}
]
}}
"""
response = self.client.models.generate_content(
model='gemini-2.5-flash',
contents=[prompt, pil_img],
config=types.GenerateContentConfig(
response_mime_type="application/json",
),
)
text = response.text
if "```json" in text:
text = text.split("```json")[1].split("```")[0].strip()
elif "```" in text:
text = text.split("```")[1].strip()
return json.loads(text)
except Exception as e:
print(f"VLM Analysis Error: {e}")
return None
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