Update app.py

app.py

@@ -31,8 +31,8 @@ def remove_background(image: Image.Image, threshold: int = 50) -> Image.Image:
     return image
 
 
-pipe = FluxInpaintPipeline.from_pretrained(
-    "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
+#pipe = FluxInpaintPipeline.from_pretrained(
+   # "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
 pipe2 = FluxImg2ImgPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
 
@@ -106,19 +106,19 @@ def process(
 
     resized_mask = mask.resize((width, height), Image.LANCZOS)
 
-    pipe.load_lora_weights("SIGMitch/KIT")
-    result = pipe(
-        prompt=input_text,
-        image=resized_image,
-        mask_image=resized_mask,
-        width=width,
-        height=height,
-        strength=strength_slider,
-        generator=generator,
-        joint_attention_kwargs={"scale": 1.2},
-        num_inference_steps=num_inference_steps_slider
-    ).images[0]
-    print('INFERENCE DONE')
+   #pipe.load_lora_weights("SIGMitch/KIT")
+    #result = pipe(
+     #   prompt=input_text,
+     #   image=resized_image,
+     #   mask_image=resized_mask,
+     #   width=width,
+     #   height=height,
+     #   strength=strength_slider,
+     #   generator=generator,
+     #   joint_attention_kwargs={"scale": 1.2},
+     #   num_inference_steps=num_inference_steps_slider
+    #).images[0]
+    #print('INFERENCE DONE')
     return result, resized_mask