Update app.py

app.py

@@ -6,16 +6,17 @@ import random
 import numpy as np
 
 MARKDOWN = """
-# FLUX.1 Inpainting 🎨
-Shoutout to [Black Forest Labs](https://huggingface.co/black-forest-labs) team for 
-creating this amazing model, and a big thanks to [Gothos](https://github.com/Gothos) 
-for taking it to the next level by enabling inpainting with the FLUX.
+# Prompt Canvas🎨
+Thanks to [Black Forest Labs](https://huggingface.co/black-forest-labs) team for creating this amazing model,
+and a big thanks to [Gothos](https://github.com/Gothos) for taking it to the next level by enabling inpainting with the FLUX.
 """
 
 MAX_SEED = np.iinfo(np.int32).max
 DEVICE = "cuda" #if torch.cuda.is_available() else "cpu"
 
-pipe = FluxInpaintPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
+inpaint_pipe = FluxInpaintPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to(DEVICE)
+
+
 
 @spaces.GPU()
 def process(input_image_editor, mask_image, input_text, strength, seed, randomize_seed, num_inference_steps, guidance_scale=3.5, progress=gr.Progress(track_tqdm=True)):
@@ -34,9 +35,9 @@ def process(input_image_editor, mask_image, input_text, strength, seed, randomiz
         
     generator = torch.Generator(device=DEVICE).manual_seed(seed)
 
-    result = pipe(prompt=input_text, image=image, mask_image=mask_image, width=width, height=height,
-                  strength=strength, num_inference_steps=num_inference_steps, generator=generator,
-                  guidance_scale=guidance_scale).images[0]
+    result = inpaint_pipe(prompt=input_text, image=image, mask_image=mask_image, width=width, height=height,
+                          strength=strength, num_inference_steps=num_inference_steps, generator=generator,
+                          guidance_scale=guidance_scale).images[0]
 
     return result, mask_image, seed