Update app.py

app.py

@@ -7,48 +7,40 @@ from diffusers import AutoPipelineForText2Image
 from PIL import PngImagePlugin
 
 BASE_MODEL_ID = "stabilityai/stable-diffusion-xl-base-1.0"
-
-# SEULEMENT LoRA face/detail compatible
 LORA_FACE_REPO = "akash-guptag/Detailers_By_Stable_Yogi"
 LORA_FACE_ADAPTER = "face_detail"
 
 DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 DTYPE = torch.float16 if DEVICE == "cuda" else torch.float32
 
-print("Chargement pipeline SDXL...")
+print("Chargement SDXL...")
 pipe = AutoPipelineForText2Image.from_pretrained(
     BASE_MODEL_ID,
     torch_dtype=DTYPE,
-    safety_checker=None,
-    requires_safety_checker=False,  
     variant="fp16" if DTYPE == torch.float16 else None,
+    safety_checker=None,
+    requires_safety_checker=False,
 )
 pipe.to(DEVICE)
+
+# MONKEY PATCH NSFW : Force "toujours safe"
+def dummy_safety_checker(images, **kwargs):
+    return images, [False] * len(images)
+
+pipe.safety_checker = dummy_safety_checker
 pipe.set_progress_bar_config(disable=True)
 
-print("Chargement LoRA face/detail (Stable Yogi)...")
+print("Chargement LoRA face...")
 pipe.load_lora_weights(LORA_FACE_REPO, adapter_name=LORA_FACE_ADAPTER)
 
 os.makedirs("outputs", exist_ok=True)
 
 @spaces.GPU()
-def generate(
-    prompt: str,
-    negative_prompt: str,
-    seed: float,
-    steps: float,
-    guidance: float,
-    width: float,
-    height: float,
-    face_enabled: bool,
-    face_weight: float,
-    script_name: str,
-):
+def generate(prompt, negative_prompt, seed, steps, guidance, width, height, face_enabled, face_weight, script_name):
     if not prompt:
         return None, "Prompt vide.", ""
 
-    seed_int = int(seed) if seed is not None else 0
-    generator = torch.Generator(device=DEVICE).manual_seed(seed_int) if seed_int >= 0 else torch.Generator(device=DEVICE)
+    generator = torch.Generator(DEVICE).manual_seed(int(seed)) if seed >= 0 else torch.Generator(DEVICE)
 
     adapters = [LORA_FACE_ADAPTER]
     weights = [float(face_weight) if face_enabled else 0.0]
@@ -65,60 +57,58 @@ def generate(
             generator=generator,
         )
     except Exception as e:
-        return None, f"Erreur SDXL : {repr(e)}", ""
+        return None, f"Erreur: {e}", ""
 
     image = result.images[0]
     
     metadata = {
-        "base_model": BASE_MODEL_ID,
-        "face_lora_repo": LORA_FACE_REPO,
-        "face_enabled": bool(face_enabled),
-        "face_weight": float(face_weight) if face_enabled else 0.0,
+        "model": BASE_MODEL_ID,
+        "lora_face": LORA_FACE_REPO,
         "prompt": prompt,
-        "seed": seed_int,
+        "seed": int(seed),
         "steps": int(steps),
-        "guidance_scale": float(guidance),
-        "width": int(width),
-        "height": int(height),
+        "guidance": float(guidance),
     }
 
-    base_name = script_name.strip().replace(" ", "_") or "sdxl_detailer"
-    img_path = os.path.join("outputs", f"{base_name}.png")
-    json_path = os.path.join("outputs", f"{base_name}.json")
+    base_name = script_name.strip().replace(" ", "_") or "nsfw_sdxl"
+    img_path = f"outputs/{base_name}.png"
+    json_path = f"outputs/{base_name}.json"
 
     pnginfo = PngImagePlugin.PngInfo()
-    pnginfo.add_text("generation_params", json.dumps(metadata, ensure_ascii=False))
+    pnginfo.add_text("params", json.dumps(metadata))
     image.save(img_path, pnginfo=pnginfo)
 
     with open(json_path, "w", encoding="utf-8") as f:
-        json.dump(metadata, f, ensure_ascii=False, indent=2)
+        json.dump(metadata, f, indent=2)
 
-    return image, json.dumps(metadata, ensure_ascii=False, indent=2), json_path
+    return image, json.dumps(metadata, indent=2), json_path
 
-# UI simplifiée
-with gr.Blocks(title="SDXL + Face Detail LoRA") as demo:
-    gr.Markdown("## SDXL 1.0 + LoRA Detailer (Stable Yogi)")
+with gr.Blocks(title="SDXL NSFW Unlocked") as demo:
+    gr.Markdown("## SDXL 1.0 NSFW ✅ + Face Detail LoRA")
     
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(label="Prompt", lines=4, value="masterpiece, 1girl, detailed face, sharp eyes, realistic skin")
-            negative = gr.Textbox(label="Negative", value="blurry, deformed, low quality")
-            
-            seed = gr.Number(label="Seed (-1=random)", value=-1)
-            steps = gr.Slider(10, 60, 30, step=1, label="Steps")
-            guidance = gr.Slider(1.0, 20.0, 7.0, step=0.5, label="Guidance")
-            
-            width = gr.Slider(512, 1536, 1024, step=64, label="Width")
-            height = gr.Slider(512, 1536, 1024, step=64, label="Height")
+            prompt = gr.Textbox(
+                "Prompt NSFW", lines=4, 
+                value="masterpiece, best quality, 1girl, nude, detailed anatomy, realistic skin, sharp face, hourglass figure"
+            )
+            negative = gr.Textbox(
+                "Negative", value="blurry, deformed, ugly, lowres, extra limbs"
+            )
+            seed = gr.Number("Seed (-1=random)", value=-1)
+            steps = gr.Slider(20, 50, 35, step=1, label="Steps")
+            guidance = gr.Slider(5.0, 12.0, 7.5, step=0.1, label="Guidance")
+            w, h = 1024, 1024
+            width = gr.Slider(512, 1536, w, step=64, label="Width")
+            height = gr.Slider(512, 1536, h, step=64, label="Height")
             
-            face_enabled = gr.Checkbox("Activer LoRA face/detail", value=True)
-            face_weight = gr.Slider(0.0, 1.5, 0.8, step=0.05, label="Poids LoRA")
+            face_weight = gr.Slider(0.0, 1.2, 0.7, step=0.05, label="LoRA Face Weight")
             
-            script_name = gr.Textbox("Nom sortie", value="test_detailer")
-            gr.Button("Générer", variant="primary").click(
-                generate,
-                inputs=[prompt, negative, seed, steps, guidance, width, height, face_enabled, face_weight, script_name],
-                outputs=[gr.Image(label="Image"), gr.Textbox(label="JSON", lines=15), gr.File(label="Télécharger JSON")]
+            name = gr.Textbox("Nom fichier", value="nsfw_test")
+            gr.Button("🚀 Générer NSFW", variant="primary").click(
+                generate, 
+                [prompt, negative, seed, steps, guidance, width, height, True, face_weight, name],
+                [gr.Image("Image"), gr.Textbox("Metadata", lines=10), gr.File("JSON")]
             )
 
 if __name__ == "__main__":