Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -47,42 +47,23 @@ pipe = StableDiffusionXLFillPipeline.from_pretrained(
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pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
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def resize_and_pad(image, target_size, resize_width=512):
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# Calculate the new height to maintain aspect ratio
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aspect_ratio = image.height / image.width
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new_height = int(resize_width * aspect_ratio)
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# Resize the image
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resized_image = image.resize((resize_width, new_height), Image.LANCZOS)
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# Create a new white image with the target size
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new_image = Image.new('RGB', target_size, (255, 255, 255))
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# Calculate position to paste the resized image (center it)
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paste_x = (target_size[0] - resize_width) // 2
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paste_y = (target_size[1] - new_height) // 2
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# Paste the resized image onto the new image
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new_image.paste(resized_image, (paste_x, paste_y))
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# Create a mask
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mask = Image.new('L', target_size, 255)
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mask_draw = ImageDraw.Draw(mask)
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mask_draw.rectangle([paste_x, paste_y, paste_x + resize_width, paste_y + new_height], fill=0)
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return new_image, mask
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@spaces.GPU
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def infer(image, model_selection, width, height, overlap_width, num_inference_steps, prompt_input=None
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target_size = (width, height)
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if source.width < target_size[0] and source.height < target_size[1]:
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scale_factor = min(target_size[0] / source.width, target_size[1] / source.height)
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new_width = int(source.width * scale_factor)
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@@ -95,24 +76,24 @@ def infer(image, model_selection, width, height, overlap_width, num_inference_st
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new_height = int(source.height * scale_factor)
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source = source.resize((new_width, new_height), Image.LANCZOS)
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final_prompt = "high quality"
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if prompt_input
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final_prompt += ", " + prompt_input
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(
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@@ -139,21 +120,27 @@ def infer(image, model_selection, width, height, overlap_width, num_inference_st
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def preload_presets(target_ratio):
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if target_ratio == "9:16":
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elif target_ratio == "16:9":
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elif target_ratio == "Custom":
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return 720, 1280, gr.update(open=True)
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def clear_result():
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return gr.update(value=None)
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css = """
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.gradio-container {
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width: 1200px !important;
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}
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"""
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title = """<h1 align="center">Diffusers Image Outpaint</h1>
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<div align="center">Drop an image you would like to extend, pick your expected ratio and hit Generate.</div>
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<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
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@@ -223,7 +210,11 @@ with gr.Blocks(css=css) as demo:
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step=1
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)
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gr.Examples(
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examples=[
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@@ -246,14 +237,13 @@ with gr.Blocks(css=css) as demo:
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outputs = [width_slider, height_slider, settings_panel],
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queue = False
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)
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run_button.click(
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fn=clear_result,
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inputs=None,
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outputs=result,
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).then(
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fn=infer,
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inputs=[input_image, model_selection, width_slider, height_slider, overlap_width, num_inference_steps,
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outputs=result,
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)
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@@ -263,7 +253,7 @@ with gr.Blocks(css=css) as demo:
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outputs=result,
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).then(
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fn=infer,
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inputs=[input_image, model_selection, width_slider, height_slider, overlap_width, num_inference_steps,
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outputs=result,
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)
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pipe.scheduler = TCDScheduler.from_config(pipe.scheduler.config)
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@spaces.GPU
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def infer(image, model_selection, width, height, overlap_width, num_inference_steps, resize_size, prompt_input=None):
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source = image
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target_size = (width, height)
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target_ratio = (width, height)
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overlap = overlap_width
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# New resizing logic based on resize_size
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if resize_size != -1:
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# Calculate new height to maintain aspect ratio
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aspect_ratio = source.height / source.width
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new_height = int(resize_size * aspect_ratio)
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source = source.resize((resize_size, new_height), Image.LANCZOS)
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# Existing resizing logic (now only applied if resize_size is -1)
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if resize_size == -1:
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if source.width < target_size[0] and source.height < target_size[1]:
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scale_factor = min(target_size[0] / source.width, target_size[1] / source.height)
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new_width = int(source.width * scale_factor)
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new_height = int(source.height * scale_factor)
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source = source.resize((new_width, new_height), Image.LANCZOS)
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margin_x = (target_size[0] - source.width) // 2
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margin_y = (target_size[1] - source.height) // 2
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background = Image.new('RGB', target_size, (255, 255, 255))
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background.paste(source, (margin_x, margin_y))
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mask = Image.new('L', target_size, 255)
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mask_draw = ImageDraw.Draw(mask)
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mask_draw.rectangle([
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(margin_x + overlap, margin_y + overlap),
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(margin_x + source.width - overlap, margin_y + source.height - overlap)
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], fill=0)
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cnet_image = background.copy()
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cnet_image.paste(0, (0, 0), mask)
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final_prompt = "high quality"
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if prompt_input.strip() != "":
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final_prompt += ", " + prompt_input
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(
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def preload_presets(target_ratio):
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if target_ratio == "9:16":
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changed_width = 720
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changed_height = 1280
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return changed_width, changed_height, gr.update(open=False)
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elif target_ratio == "16:9":
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changed_width = 1280
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changed_height = 720
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return changed_width, changed_height, gr.update(open=False)
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elif target_ratio == "Custom":
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return 720, 1280, gr.update(open=True)
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def clear_result():
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return gr.update(value=None)
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css = """
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.gradio-container {
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width: 1200px !important;
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}
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"""
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title = """<h1 align="center">Diffusers Image Outpaint</h1>
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<div align="center">Drop an image you would like to extend, pick your expected ratio and hit Generate.</div>
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<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
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step=1
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)
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resize_size = gr.Number(
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label="Resize Size (-1 for default behavior)",
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value=-1,
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precision=0
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)
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gr.Examples(
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examples=[
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outputs = [width_slider, height_slider, settings_panel],
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queue = False
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)
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run_button.click(
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fn=clear_result,
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inputs=None,
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outputs=result,
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).then(
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fn=infer,
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inputs=[input_image, model_selection, width_slider, height_slider, overlap_width, num_inference_steps, resize_size, prompt_input],
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outputs=result,
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)
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outputs=result,
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).then(
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fn=infer,
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inputs=[input_image, model_selection, width_slider, height_slider, overlap_width, num_inference_steps, resize_size, prompt_input],
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outputs=result,
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)
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