Spaces:
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Update backup.app.py
Browse files- backup.app.py +126 -23
backup.app.py
CHANGED
@@ -9,11 +9,10 @@ import re
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import random
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import torch
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import time
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import
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from PIL import Image
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from io import BytesIO
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from PIL import Image
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from diffusers import DiffusionPipeline, LCMScheduler, AutoencoderTiny
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try:
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@@ -33,6 +32,97 @@ device = torch.device(
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torch_device = device
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torch_dtype = torch.float16
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print(f"SAFETY_CHECKER: {SAFETY_CHECKER}")
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print(f"TORCH_COMPILE: {TORCH_COMPILE}")
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print(f"device: {device}")
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@@ -105,23 +195,25 @@ def predict(prompt, guidance, steps, seed=1231231):
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if nsfw_content_detected:
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nsfw=gr.Button("🕹️NSFW🎨", scale=1)
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return results.images[0] if len(results.images) > 0 else None
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@@ -138,9 +230,10 @@ css = """
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="container"):
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gr.Markdown(
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"""
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elem_id="intro",
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)
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with gr.Row():
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@@ -166,6 +259,12 @@ with gr.Blocks(css=css) as demo:
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label="Generated Images", show_label=False, elem_id="gallery"
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)
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# Advanced Generate Options
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with gr.Accordion("Advanced options", open=False):
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guidance = gr.Slider(
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@@ -186,11 +285,9 @@ with gr.Blocks(css=css) as demo:
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```py
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from diffusers import DiffusionPipeline, LCMScheduler
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pipe = DiffusionPipeline.from_pretrained("Lykon/dreamshaper-7").to("cuda")
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5") #yes, it's a normal LoRA
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results = pipe(
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prompt="ImageEditor",
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num_inference_steps=4,
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steps.change(fn=predict, inputs=inputs, outputs=image, show_progress=False)
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seed.change(fn=predict, inputs=inputs, outputs=image, show_progress=False)
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demo.queue()
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demo.launch()
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import random
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import torch
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import time
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import shutil # Added for zip functionality
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import zipfile
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from PIL import Image
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from io import BytesIO
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from diffusers import DiffusionPipeline, LCMScheduler, AutoencoderTiny
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try:
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torch_device = device
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torch_dtype = torch.float16
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# Function to encode a file to base64
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def encode_file_to_base64(file_path):
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with open(file_path, "rb") as file:
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encoded = base64.b64encode(file.read()).decode()
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return encoded
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def create_zip_of_files(files):
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"""
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Create a zip file from a list of files.
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"""
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zip_name = "all_files.zip"
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with zipfile.ZipFile(zip_name, 'w') as zipf:
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for file in files:
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zipf.write(file)
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return zip_name
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def get_zip_download_link(zip_file):
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"""
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Generate a link to download the zip file.
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"""
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with open(zip_file, 'rb') as f:
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data = f.read()
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b64 = base64.b64encode(data).decode()
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href = f'<a href="data:application/zip;base64,{b64}" download="{zip_file}">Download All</a>'
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return href
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# Function to clear all image files
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def clear_all_images():
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base_dir = os.getcwd() # Get the current base directory
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img_files = [file for file in os.listdir(base_dir) if file.lower().endswith((".png", ".jpg", ".jpeg"))] # List all files ending with ".jpg" or ".jpeg"
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# Remove all image files
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for file in img_files:
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os.remove(file)
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print('removed:' + file)
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# add file save and download and clear:
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# Function to create a zip file from a list of files
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def create_zip(files):
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timestamp = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
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zip_filename = f"images_{timestamp}.zip"
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print('Creating file ' + zip_filename)
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with zipfile.ZipFile(zip_filename, 'w') as zipf:
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for file in files:
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zipf.write(file, os.path.basename(file))
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print('added:' + file)
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return zip_filename
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# Function to save all images as a zip file and provide a base64 download link
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def save_all_images(images):
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if len(images) == 0:
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return None, None
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zip_filename = create_zip(images) # Create a zip file from the list of image files
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print(' Zip file created:' + zip_filename)
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# gr.Button(link="/file=" + zip_filename)
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# remove?
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zip_base64 = encode_file_to_base64(zip_filename) # Encode the zip file to base64
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download_link = f'<a href="data:application/zip;base64,{zip_base64}" download="{zip_filename}">Download All</a>'
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# redirect_button = gr.Button("Clear", variant='secondary')
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# redirect_button.click(None, None,None, _js="window.location.assign('https://google.com');")
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return zip_filename, download_link
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# Function to handle "Save All" button click
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def save_all_button_click():
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images = [file for file in os.listdir() if file.lower().endswith((".png", ".jpg", ".jpeg"))]
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zip_filename, download_link = save_all_images(images)
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if zip_filename:
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print(zip_filename)
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gr.Button(link=zip_filename)
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# gr.File(value=zip_filename)
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if download_link:
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print(download_link)
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#gr.HTML(download_link)
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gr.Button(link=download_link)
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# Function to handle "Clear All" button click
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def clear_all_button_click():
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clear_all_images()
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print(f"SAFETY_CHECKER: {SAFETY_CHECKER}")
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print(f"TORCH_COMPILE: {TORCH_COMPILE}")
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print(f"device: {device}")
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if nsfw_content_detected:
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nsfw=gr.Button("🕹️NSFW🎨", scale=1)
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try:
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central = pytz.timezone('US/Central')
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safe_date_time = datetime.datetime.now().strftime("%Y%m%d")
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replaced_prompt = prompt.replace(" ", "_").replace("\n", "_")
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safe_prompt = "".join(x for x in replaced_prompt if x.isalnum() or x == "_")[:90]
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filename = f"{safe_date_time}_{safe_prompt}.png"
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# Save the image
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if len(results.images) > 0:
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image_path = os.path.join("", filename) # Specify your directory
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results.images[0].save(image_path)
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print(f"#Image saved as {image_path}")
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gr.File(image_path)
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gr.Button(link=image_path)
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# encoded_image = encode_image(image)
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# html_link = f'<a href="data:image/png;base64,{encoded_image}" download="{filename}">Download Image</a>'
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# gr.HTML(html_link)
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except:
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return results.images[0]
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return results.images[0] if len(results.images) > 0 else None
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="container"):
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gr.Markdown(
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"""4📝RT🖼️Images - 🕹️ Real Time 🎨 Image Generator Gallery 🌐""",
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elem_id="intro",
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)
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with gr.Row():
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label="Generated Images", show_label=False, elem_id="gallery"
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)
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with gr.Row(variant="compact"):
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# Add "Save All" button with emoji
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save_all_button = gr.Button("💾 Save All", scale=1)
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# Add "Clear All" button with emoji
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clear_all_button = gr.Button("🗑️ Clear All", scale=1)
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# Advanced Generate Options
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with gr.Accordion("Advanced options", open=False):
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guidance = gr.Slider(
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```py
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from diffusers import DiffusionPipeline, LCMScheduler
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pipe = DiffusionPipeline.from_pretrained("Lykon/dreamshaper-7").to("cuda")
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pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config)
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pipe.load_lora_weights("latent-consistency/lcm-lora-sdv1-5") #yes, it's a normal LoRA
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results = pipe(
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prompt="ImageEditor",
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num_inference_steps=4,
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steps.change(fn=predict, inputs=inputs, outputs=image, show_progress=False)
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seed.change(fn=predict, inputs=inputs, outputs=image, show_progress=False)
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# Attach click event handlers to the buttons
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save_all_button.click(save_all_button_click)
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clear_all_button.click(clear_all_button_click)
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demo.queue()
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demo.launch()
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