Update app.py

app.py

@@ -42,14 +42,8 @@ pipe = QwenImageEditPlusPipeline.from_pretrained(
         device_map="cuda",
     ),
     torch_dtype=dtype,
-	safety_checker=None,        # <-- Добавьте эту строку
-    feature_extractor=None,     # <-- Добавьте эту строку
 ).to(device)
 
-# Отключение проверки на уровне экземпляра pipeline
-if hasattr(pipe, "safety_checker"):
-    pipe.safety_checker = None
-	
 try:
     pipe.transformer.set_attn_processor(QwenDoubleStreamAttnProcessorFA3())
     print("Flash Attention 3 Processor set successfully.")
@@ -182,14 +176,13 @@ def b64_to_pil_list(b64_json_str):
 
 def update_dimensions_on_upload(image):
     if image is None:
-        return 1024, 1024  
+        return 1024, 1024
     w, h = image.size
-    target_dim = 1024  
     if w > h:
-        nw = target_dim
+        nw = 1024
         nh = int(nw * h / w)
     else:
-        nh = target_dim
+        nh = 1024
         nw = int(nh * w / h)
     return (nw // 8) * 8, (nh // 8) * 8
 
@@ -206,7 +199,7 @@ def infer(images_b64_json, prompt, seed, randomize_seed, guidance_scale, steps,
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
     generator = torch.Generator(device=device).manual_seed(seed)
-    negative_prompt = "blurry, low resolution, low quality, soft details, artifacts, pixelated, plastic skin, smooth skin, 3d render, cartoon, anime, blurry, low resolution, bad anatomy, overprocessed, oversaturated, painting, drawing"
+    negative_prompt = "worst quality, low quality, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry"
     width, height = update_dimensions_on_upload(pil_images[0])
     try:
         result_image = pipe(