Update app.py

app.py

@@ -165,12 +165,17 @@ def generate(face_image, style_image, prompt, negative_prompt,
 
         gen = None if seed is None or int(seed) < 0 else torch.Generator(device=DEVICE).manual_seed(int(seed))
 
+        # visage → carré 512 pour détection stable
         face = ImageOps.exif_transpose(face_image).convert("RGB")
-        ms = min(face.size); x = (face.width - ms) // 2; y = (face.height - ms) // 2
+        ms = min(face.size)
+        x = (face.width - ms) // 2
+        y = (face.height - ms) // 2
         face_sq = face.crop((x, y, x + ms, y + ms)).resize((512, 512), Image.Resampling.LANCZOS)
 
+        # InsightFace : embedding (torch [1,D]) + landmarks
         face_emb, kps_img = extract_face_embed_and_kps(face_sq)
 
+        # IP-Adapter scales
         try:
             if HAS_STYLE_ADAPTER and style_image is not None:
                 pipe.set_ip_adapter_scale({"instantid": float(adapter_strength), "style": float(style_strength)})
@@ -179,41 +184,48 @@ def generate(face_image, style_image, prompt, negative_prompt,
         except Exception as e:
             print(f"ℹ️ set_ip_adapter_scale ignoré: {e}")
 
+        # compat multi-ControlNet (même si on en a qu’un)
         cn = getattr(pipe, "controlnet", None)
         if isinstance(cn, (list, tuple)):
             n_cn = len(cn)
         else:
-            try: n_cn = len(cn)
-            except Exception: n_cn = 1
+            try:
+                n_cn = len(cn)
+            except Exception:
+                n_cn = 1
 
-        image_arg = [kps_img] * n_cn if n_cn > 1 else ([kps_img] if isinstance(cn, (list, tuple)) else kps_img)
+        image_arg = [kps_img] * n_cn if n_cn > 1 else (
+            [kps_img] if isinstance(cn, (list, tuple)) else kps_img
+        )
         scale_val = float(identity_strength)
-        scale_arg = [scale_val] * n_cn if n_cn > 1 else ([scale_val] if isinstance(cn, (list, tuple)) else scale_val)
-
-       # ✅ Construction des kwargs d’inférence — compat 0.29/0.30
-gen_kwargs = dict(
-    prompt=(prompt or "").strip(),
-    negative_prompt=(negative_prompt or "").strip(),
-    image=image_arg,                         # IdentityNet (landmarks)
-    image_embeds=face_emb,                   # compat pipeline
-    # --- CLÉ : passer aux deux noms pour couvrir 0.29 (added_cond_kwargs) et 0.30 (added_conditions)
-    added_conditions={"image_embeds": face_emb},     # ← diffusers >= 0.30.0
-    added_cond_kwargs={"image_embeds": face_emb},    # ← diffusers 0.29.x (safe no-op si ignoré)
-    controlnet_conditioning_scale=scale_arg,
-    num_inference_steps=int(steps),
-    guidance_scale=float(cfg),
-    width=int(width),
-    height=int(height),
-    generator=gen,
-)
+        scale_arg = [scale_val] * n_cn if n_cn > 1 else (
+            [scale_val] if isinstance(cn, (list, tuple)) else scale_val
+        )
 
+        # ✅ Correctif clé : double passage pour compatibilité 0.29 / 0.30
+        gen_kwargs = dict(
+            prompt=(prompt or "").strip(),
+            negative_prompt=(negative_prompt or "").strip(),
+            image=image_arg,
+            image_embeds=face_emb,
+            added_conditions={"image_embeds": face_emb},     # diffusers ≥ 0.30.0
+            added_cond_kwargs={"image_embeds": face_emb},    # diffusers 0.29.x
+            controlnet_conditioning_scale=scale_arg,
+            num_inference_steps=int(steps),
+            guidance_scale=float(cfg),
+            width=int(width),
+            height=int(height),
+            generator=gen,
+        )
 
+        # Si un style est fourni
         if HAS_STYLE_ADAPTER and style_image is not None:
             try:
                 gen_kwargs["ip_adapter_image"] = ImageOps.exif_transpose(style_image).convert("RGB")
             except Exception as e:
                 print(f"ℹ️ ip_adapter_image ignoré: {e}")
 
+        # Appel pipeline
         images = pipe(**gen_kwargs).images
         return images[0], "", "\n".join(load_logs)
 
@@ -222,6 +234,7 @@ gen_kwargs = dict(
     except Exception:
         return None, "Erreur:\n" + traceback.format_exc(), "\n".join(load_logs)
 
+
 EX_PROMPT = (
     "one piece style, Eiichiro Oda style, anime portrait, upper body, pirate outfit, "
     "clean lineart, cel shading, vibrant colors, expressive eyes, dynamic composition, simple background"