app.py

import gradio as gr
from PIL import Image, ImageStat, ImageDraw
import io

# ===========================
# EURISTIC AI DETECTOR
# ===========================
def heuristic_ai_detector(image):
    stat = ImageStat.Stat(image.convert("L"))
    variance = stat.var[0]
    width, height = image.size
    exif = image.getexif()
    exif_score = 0 if len(exif) == 0 else 50
    score = 50
    if variance < 500:
        score += 30
    if width > 2000 or height > 2000:
        score += 20
    score -= exif_score / 2
    score = max(0, min(100, score))
    label = "AI Generated" if score >= 50 else "Realistic"
    return label, score

# ===========================
# GENERA HEATMAP
# ===========================
def generate_heatmap(image, score):
    base = image.convert("RGBA")
    overlay = Image.new("RGBA", base.size, (255, 0, 0, int(score*2.5)))
    return Image.alpha_composite(base, overlay)

# ===========================
# FUNZIONE PRINCIPALE
# ===========================
def check_image(image):
    label, score = heuristic_ai_detector(image)
    heatmap = generate_heatmap(image, score)

    if score < 40:
        color = "#4CAF50"  # verde
    elif score < 70:
        color = "#FFC107"  # giallo
    else:
        color = "#F44336"  # rosso

    if label == "AI Generated":
        explanation = f"""
        <div class="result-card" style="border-left: 5px solid {color};">
            <h2>⚠️ AI Generated Image</h2>
            <p><b>Score AI stimato:</b> {score:.1f}%</p>
            <p>Rumore basso / texture uniforme</p>
            <p>Dimensioni insolite</p>
            <p>Metadata EXIF assente</p>
        </div>
        """
    else:
        explanation = f"""
        <div class="result-card" style="border-left: 5px solid {color};">
            <h2>✅ Realistic Image</h2>
            <p><b>Score AI stimato:</b> {score:.1f}%</p>
            <p>Rumore naturale</p>
            <p>Dimensioni coerenti</p>
            <p>Metadata EXIF presente</p>
        </div>
        """

    return heatmap, explanation

# ===========================
# GRADIO BLOCKS MODERNO
# ===========================
with gr.Blocks(css="""
body { background-color: #0d1117; font-family: 'Montserrat', sans-serif; color: #EEE; margin:0; }
h1 { text-align:center; font-size: 48px; color: #FFD700; margin-bottom: 5px;}
h3 { text-align:center; color: #CCCCCC; margin-top:0px; font-weight:normal; }
.gr-button { background: linear-gradient(90deg,#FFD700,#FFAA00); color:black; font-weight:bold; border-radius:10px; height:50px; font-size:18px; transition: all 0.3s ease;}
.gr-button:hover { transform: scale(1.05); box-shadow:0px 5px 15px rgba(255,170,0,0.6);}
.result-card { background-color:#161B22; border-radius:15px; padding:20px; margin-top:20px; box-shadow:0 4px 15px rgba(0,0,0,0.4); transition: transform 0.3s ease;}
.result-card:hover { transform: scale(1.02); }
.gr-box { background-color:transparent; border-radius:15px; padding:15px; }
""") as demo:

    gr.HTML("<h1>💎 Image Trust Checker 2026</h1><h3>Verifica se le immagini sono generate da AI o realistiche</h3>")

    with gr.Row():
        with gr.Column(scale=1):
            img_input = gr.Image(label="Carica immagine", type="pil")
            analyze_btn = gr.Button("Analizza immagine")
        with gr.Column(scale=1):
            img_output = gr.Image(label="Heatmap sospetta", type="pil")
            txt_output = gr.HTML(label="Risultato")

    analyze_btn.click(fn=check_image, inputs=img_input, outputs=[img_output, txt_output])

demo.launch()