test

README.md

@@ -4,7 +4,7 @@ emoji: 🔅
 colorFrom: gray
 colorTo: purple
 sdk: gradio
-sdk_version: 5.34.2
+sdk_version: 4.42.0
 app_file: app.py
 pinned: true
 license: apache-2.0

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 import spaces
-import time
 import torch
 from diffusers import AutoencoderKL, TCDScheduler
 from diffusers.models.model_loading_utils import load_state_dict
@@ -169,57 +168,10 @@ def preview_image_and_mask(image, width, height, overlap_percentage, resize_opti
     
     return preview
 
-@spaces.GPU()
-def infer(
-    image, 
-    width, 
-    height, 
-    overlap_percentage, 
-    num_inference_steps, 
-    resize_option, 
-    custom_resize_percentage, 
-    prompt_input, 
-    alignment, 
-    overlap_left, 
-    overlap_right, 
-    overlap_top, 
-    overlap_bottom
-):
-    """
-    Generate an outpainted image using Stable Diffusion XL with ControlNet guidance.
+@spaces.GPU(duration=24)
+def infer(image, width, height, overlap_percentage, num_inference_steps, resize_option, custom_resize_percentage, prompt_input, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom):
+    background, mask = prepare_image_and_mask(image, width, height, overlap_percentage, resize_option, custom_resize_percentage, alignment, overlap_left, overlap_right, overlap_top, overlap_bottom)
     
-    This function performs intelligent image outpainting by expanding the input image 
-    according to the specified target dimensions and alignment, generating new content 
-    guided by a textual prompt. It uses a ControlNet-enabled diffusion pipeline to ensure 
-    coherent image extension.
-
-    Args:
-        image (PIL.Image): The input image to be outpainted.
-        width (int): The target width of the output image.
-        height (int): The target height of the output image.
-        overlap_percentage (int): Percentage of overlap between original and outpainted regions for seamless blending.
-        num_inference_steps (int): Number of inference steps for image generation. Higher values yield better results.
-        resize_option (str): Predefined or custom percentage to resize the input image ("Full", "50%", "33%", "25%", or "Custom").
-        custom_resize_percentage (int): Custom resize percentage if resize_option is "Custom".
-        prompt_input (str): A text prompt describing desired content for the generated region.
-        alignment (str): Alignment of the original image within the canvas ("Middle", "Left", "Right", "Top", "Bottom").
-        overlap_left (bool): Whether to allow blending on the left edge.
-        overlap_right (bool): Whether to allow blending on the right edge.
-        overlap_top (bool): Whether to allow blending on the top edge.
-        overlap_bottom (bool): Whether to allow blending on the bottom edge.
-
-    Yields:
-        Tuple[PIL.Image, PIL.Image]: 
-        - The intermediate ControlNet input image (showing the masked area).
-        - The final generated image with the inpainted region.
-    """
-    #gr.Info("10 seconds will be used from your daily ZeroGPU time credits.")
-    background, mask = prepare_image_and_mask(
-        image, width, height, overlap_percentage, 
-        resize_option, custom_resize_percentage, alignment,
-        overlap_left, overlap_right, overlap_top, overlap_bottom
-    )
-
     if not can_expand(background.width, background.height, width, height, alignment):
         alignment = "Middle"
 
@@ -245,12 +197,10 @@ def infer(
     ):
         yield cnet_image, image
 
-    #time.sleep(1)
-    #image = image.convert("RGBA")
-    #cnet_image.paste(image, (0, 0), mask)
-
-    #return background, cnet_image
+    image = image.convert("RGBA")
+    cnet_image.paste(image, (0, 0), mask)
 
+    yield background, cnet_image
 
 def clear_result():
     """Clears the result ImageSlider."""
@@ -288,7 +238,6 @@ def toggle_custom_resize_slider(resize_option):
 
 def update_history(new_image, history):
     """Updates the history gallery with the new image."""
-    time.sleep(1)
     if history is None:
         history = []
     history.insert(0, new_image)
@@ -296,7 +245,7 @@ def update_history(new_image, history):
 
 css = """
 .gradio-container {
-    max-width: 1200px !important;
+    width: 1200px !important;
 }
 """
 
@@ -425,87 +374,75 @@ with gr.Blocks(css=css) as demo:
     use_as_input_button.click(
         fn=use_output_as_input,
         inputs=[result],
-        outputs=[input_image],
-        show_api=False
+        outputs=[input_image]
     )
     
     target_ratio.change(
         fn=preload_presets,
         inputs=[target_ratio, width_slider, height_slider],
         outputs=[width_slider, height_slider, settings_panel],
-        queue=False,
-        show_api=False
+        queue=False
     )
 
     width_slider.change(
         fn=select_the_right_preset,
         inputs=[width_slider, height_slider],
         outputs=[target_ratio],
-        queue=False,
-        show_api=False
+        queue=False
     )
 
     height_slider.change(
         fn=select_the_right_preset,
         inputs=[width_slider, height_slider],
         outputs=[target_ratio],
-        queue=False,
-        show_api=False
+        queue=False
     )
 
     resize_option.change(
         fn=toggle_custom_resize_slider,
         inputs=[resize_option],
         outputs=[custom_resize_percentage],
-        queue=False,
-        show_api=False
+        queue=False
     )
     
     run_button.click(  # Clear the result
         fn=clear_result,
         inputs=None,
         outputs=result,
-        show_api=False
     ).then(  # Generate the new image
         fn=infer,
         inputs=[input_image, width_slider, height_slider, overlap_percentage, num_inference_steps,
                 resize_option, custom_resize_percentage, prompt_input, alignment_dropdown,
                 overlap_left, overlap_right, overlap_top, overlap_bottom],
         outputs=result,
-    ).then(  # Show the "Use as Input Image" button
-        fn=lambda: gr.update(visible=True),
-        inputs=None,
-        outputs=use_as_input_button,
-        show_api=False
     ).then(  # Update the history gallery
         fn=lambda x, history: update_history(x[1], history),
         inputs=[result, history_gallery],
         outputs=history_gallery,
-        show_api=False
+    ).then(  # Show the "Use as Input Image" button
+        fn=lambda: gr.update(visible=True),
+        inputs=None,
+        outputs=use_as_input_button,
     )
 
     prompt_input.submit(  # Clear the result
         fn=clear_result,
         inputs=None,
         outputs=result,
-        show_api=False
     ).then(  # Generate the new image
         fn=infer,
         inputs=[input_image, width_slider, height_slider, overlap_percentage, num_inference_steps,
                 resize_option, custom_resize_percentage, prompt_input, alignment_dropdown,
                 overlap_left, overlap_right, overlap_top, overlap_bottom],
         outputs=result,
-        show_api=False
     ).then(  # Update the history gallery
         fn=lambda x, history: update_history(x[1], history),
         inputs=[result, history_gallery],
         outputs=history_gallery,
-        show_api=False
     ).then(  # Show the "Use as Input Image" button
         fn=lambda: gr.update(visible=True),
         inputs=None,
         outputs=use_as_input_button,
-        show_api=False
     )
 
     preview_button.click(
@@ -513,8 +450,7 @@ with gr.Blocks(css=css) as demo:
         inputs=[input_image, width_slider, height_slider, overlap_percentage, resize_option, custom_resize_percentage, alignment_dropdown,
                 overlap_left, overlap_right, overlap_top, overlap_bottom],
         outputs=preview_image,
-        queue=False,
-        show_api=False
+        queue=False
     )
 
-demo.queue(max_size=12).launch(share=False, show_error=True, mcp_server=True)
+demo.queue(max_size=12).launch(share=False, show_error=True)

requirements.txt

@@ -1,12 +1,10 @@
 torch==2.5.1
-spaces==0.37.0
-gradio[mcp]
+spaces==0.30.4
+gradio==4.42.0
 gradio-imageslider
 numpy==1.26.4
 transformers==4.45.0
 accelerate==0.33.0
-#diffusers==0.30.3
-diffusers==0.32.2
-huggingface-hub
+diffusers==0.30.3
 fastapi<0.113.0
 opencv-python