Update app.py

app.py

@@ -1,3 +1,4 @@
+import subprocess, sys
 import gradio as gr
 import cv2
 import numpy as np
@@ -106,7 +107,7 @@ def test_fft(roi):
     outer_energy = mag[~mask].mean()
     if outer_energy == 0: return 0.5
     ratio = center_energy / outer_energy
-    if ratio > 1.5: return 0.95  # Ajusté pour mobile
+    if ratio > 1.5: return 0.95 
     elif ratio > 1.0: return 0.80
     else: return 0.30
 
@@ -118,7 +119,6 @@ def test_contours(roi):
     border = int(min(h, w) * 0.15)
     center = edges[border:-border, border:-border]
     center_den = center.mean() if center.size > 0 else 1
-    # On est moins sévère sur le ratio de bordure pour les vidéos naturelles
     ratio = edges.mean() / (center_den + 1e-5)
     return 0.90 if ratio < 2.0 else 0.40
 
@@ -126,7 +126,7 @@ def test_contours(roi):
 # ÉTAPE 4 — SCORE ET VERDICT (FIX SEUILS)
 # ═══════════════════════════════════════════════════════════
 def get_verdict(score_pct):
-    # AJUSTEMENT : 75.7% devient AUTHENTIQUE
+    # AJUSTEMENT S2T : 75.7% devient ✅ AUTHENTIQUE
     if score_pct >= 70:
         return "✅ AUTHENTIQUE", "Qualité validée conforme aux standards mobiles S2T."
     elif score_pct >= 50:
@@ -145,7 +145,7 @@ def analyze_deepfake(video_path):
     detail_logs = []
     
     for frame in frames:
-        rois = detect_and_restore_faces(frame) # Utilise la détection + restauration
+        rois = detect_and_restore_faces(frame) 
         for roi in rois:
             s_b = test_noise(roi)
             s_f = test_fft(roi)
@@ -160,7 +160,6 @@ def analyze_deepfake(video_path):
     global_score_pct = round(np.mean(all_scores) * 100, 1)
     verdict, explication = get_verdict(global_score_pct)
     
-    # Création du rapport final
     sep = "─" * 48
     rapport = (
         f"🛡️ VideoShield v3.0 — Rapport d'Authenticité\n{sep}\n"
@@ -180,10 +179,9 @@ def analyze_deepfake(video_path):
         "restoration_active": True
     }
     
-    # INDEXATION AUTOMATIQUE
     index_analysis(json_data)
     
-    return rapport, json.dumps(json_data, indent=2)
+    return rapport, json.dumps(json_data, indent=2, ensure_ascii=False)
 
 # ═══════════════════════════════════════════════════════════
 # INTERFACE
@@ -201,4 +199,4 @@ with gr.Blocks(title="VideoShield v3.0", theme=gr.themes.Soft()) as demo:
     btn.click(analyze_deepfake, inputs=[video_input], outputs=[rapport_out, json_out])
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0")
+    demo.launch(server_name="0.0.0.0")