update

app.py

@@ -1,6 +1,13 @@
 import spaces
 import torch
 from diffusers import FluxInpaintPipeline
+import gradio as gr
+import re
+from PIL import Image
+
+import os
+import numpy as np
+
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -9,12 +16,7 @@ pipe = FluxInpaintPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", t
 
 
 
-import gradio as gr
-import re
-from PIL import Image
 
-import os
-import numpy as np
 
 
 def sanitize_prompt(prompt):
@@ -46,7 +48,7 @@ def process_images(image, image2=None,prompt="a girl",inpaint_model="black-fores
          mask = image['layers'][0]
 
 
-    def process_image(image,mask_image,prompt="a person",model_id="black-forest-labs/FLUX.1-schnell",strength=0.75,seed=0,num_inference_steps=4):
+    def process_inpaint(image,mask_image,prompt="a person",model_id="black-forest-labs/FLUX.1-schnell",strength=0.75,seed=0,num_inference_steps=4):
         if image == None:
             return None
    
@@ -55,12 +57,13 @@ def process_images(image, image2=None,prompt="a girl",inpaint_model="black-fores
         generator = torch.Generator("cuda").manual_seed(seed)
         generators.append(generator)
         # more parameter see https://huggingface.co/docs/diffusers/api/pipelines/flux#diffusers.FluxInpaintPipeline
-        output = pipe(prompt=prompt, image=image, mask_image=mask_image,generator=generator,strength=strength)
+        output = pipe(prompt=prompt, image=image, mask_image=mask_image,generator=generator,strength=strength,
+                      guidance_scale=0,num_inference_steps=num_inference_steps,max_sequence_length=256)
 
         return output.images[0]
 
 
-    output = process_image(image["background"],mask,prompt,inpaint_model,strength,seed)
+    output = process_inpaint(image["background"],mask,prompt,inpaint_model,strength,seed)
         
     return output,mask
     
@@ -71,16 +74,6 @@ def read_file(path: str) -> str:
 
     return content
 
-def example_out(image,image_mask,prompt,strength,example_id):
-    # input
-    #parent,file=os.path.split(image_mask) # image is complex dict
-    #base,ext = os.path.splitext(file)
-    #key = base.split("_")[0]
-    return f"images/{example_id}.jpg"
-    #loaded_image =  Image.open(f"images/{example_id}.jpg")
-    #return loaded_image
-    #return np.array(loaded_image)
-
 css="""
 #col-left {
     margin: 0 auto;
@@ -100,7 +93,7 @@ with demo_blocks as demo:
                     image = gr.ImageEditor(height=800,sources=['upload','clipboard'],transforms=[],image_mode='RGB', layers=False,  elem_id="image_upload", type="pil", label="Upload",brush=gr.Brush(colors=["#fff"], color_mode="fixed"))
                     with gr.Row(elem_id="prompt-container",  equal_height=False):
                         with gr.Row():
-                            prompt = gr.Textbox(label="Prompt",value="a eyes closed girl,shut eyes",placeholder="Your prompt (what you want in place of what is erased)", elem_id="prompt")
+                            prompt = gr.Textbox(label="Prompt",value="a person",placeholder="Your prompt (what you want in place of what is erased)", elem_id="prompt")
                             
                     btn = gr.Button("Inpaint", elem_id="run_button",variant="primary")
                     
@@ -139,4 +132,4 @@ with demo_blocks as demo:
         """
     )
 
-demo_blocks.queue(max_size=25).launch(share=False,debug=True)
+demo_blocks.launch()