Update app.py

app.py

@@ -1,4 +1,3 @@
-import spaces
 import gradio as gr
 import numpy as np
 import PIL.Image
@@ -8,22 +7,11 @@ from diffusers import ControlNetModel, StableDiffusionXLPipeline, AutoencoderKL
 from diffusers import DDIMScheduler, EulerAncestralDiscreteScheduler
 import cv2
 import torch
-
+import os
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-#vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-
-#pipe = StableDiffusionXLPipeline.from_pretrained(
-#    #"yodayo-ai/clandestine-xl-1.0", 
-#    torch_dtype=torch.float16, 
-#    use_safetensors=True,
-#    custom_pipeline="lpw_stable_diffusion_xl",
-#    add_watermarker=False #,
-#    #variant="fp16"
-#)
 pipe = StableDiffusionXLPipeline.from_single_file(
-    #"https://huggingface.co/Laxhar/noob_sdxl_beta/noob_hercules4/fp16/checkpoint-e0_s10000.safetensors/checkpoint-e0_s10000.safetensors",
     "https://huggingface.co/Laxhar/noob_sdxl_beta/noob_hercules3/checkpoint/checkpoint-e2_s109089.safetensors/checkpoint-e2_s109089.safetensors",
     use_safetensors=True,
     torch_dtype=torch.float16,
@@ -34,7 +22,6 @@ pipe.to(device)
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 1216
 
-    
 @spaces.GPU
 def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
 
@@ -53,8 +40,11 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
         generator=generator
     ).images[0]
 
-    return output_image
+    # PNG形式で一時的に保存
+    output_path = "output_image.png"
+    output_image.save(output_path, format="PNG")
 
+    return output_path  # ファイルパスを返す
 
 css = """
 #col-container {
@@ -70,8 +60,6 @@ with gr.Blocks(css=css) as demo:
          Text-to-Image Demo
         using [Noob SDXL beta model](https://huggingface.co/Laxhar)
         """)
-        #yodayo-ai/clandestine-xl-1.0　
-        #yodayo-ai/holodayo-xl-2.1
         with gr.Row():
             prompt = gr.Text(
                 label="Prompt",
@@ -83,7 +71,7 @@ with gr.Blocks(css=css) as demo:
 
             run_button = gr.Button("Run", scale=0)
 
-        result = gr.Image(label="Result", show_label=False, show_download_button=True)
+        result = gr.Image(label="Result", show_label=False, type="filepath")
         
         with gr.Accordion("Advanced Settings", open=False):
 
@@ -110,7 +98,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,#832,
+                    value=1024,
                 )
 
                 height = gr.Slider(
@@ -118,7 +106,7 @@ with gr.Blocks(css=css) as demo:
                     minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024,#1216,
+                    value=1024,
                 )
 
             with gr.Row():
@@ -138,7 +126,7 @@ with gr.Blocks(css=css) as demo:
                     value=28,
                 )
 
-    run_button.click(#lambda x: None, inputs=None, outputs=result).then(
+    run_button.click(
         fn=infer,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
         outputs=[result]