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b62f01b
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Parent(s):
2f14be5
Add "send to txt2img" button to PNGInfo (#9)
Browse files- Add "send to txt2img" button to PNGInfo (bf9ad1e6fbede10b78960336c6829133a61025ba)
- Replace static model list with function for removing extension and id (33f7d493b13c46fe5889e7067b6ca1bbb67b42a9)
- Update app.py (516f2ad246531f25395b79d0e3d2cfbf8726db81)
Co-authored-by: Zenafey Baenro <[email protected]>
app.py
CHANGED
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@@ -80,9 +80,86 @@ def image_to_base64(image_path):
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return img_str.decode('utf-8') # Convert bytes to string
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prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
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def flip_text(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
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result = prodia_client.generate({
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with gr.Blocks(css=css) as demo:
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with gr.Row():
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with gr.Column(scale=6):
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model = gr.Dropdown(interactive=True,value="absolutereality_v181.safetensors [3d9d4d2b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
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@@ -118,96 +195,99 @@ with gr.Blocks(css=css) as demo:
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with gr.Column(scale=1):
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gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI.<br>Powered by [Prodia](https://prodia.com).<br> For more features and faster gen times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide)")
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with gr.
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with gr.
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with gr.
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with gr.
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with gr.
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with gr.
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with gr.
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"Euler",
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with gr.Row():
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with gr.Column(scale=1):
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width = gr.Slider(label="Width", maximum=1024, value=512, step=8)
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height = gr.Slider(label="Height", maximum=1024, value=512, step=8)
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with gr.Column(scale=1):
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batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
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batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
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cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
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seed = gr.Number(label="Seed", value=-1)
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with gr.Column(scale=2):
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image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
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text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
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<
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demo.queue(concurrency_count=32)
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demo.launch()
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return img_str.decode('utf-8') # Convert bytes to string
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def remove_id_and_ext(text):
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text = re.sub(r'\[.*\]$', '', text)
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extension = text[-12:].strip()
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if extension == "safetensors":
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text = text[:-13]
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elif extension == "ckpt":
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text = text[:-4]
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return text
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def get_data(text):
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results = {}
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patterns = {
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'prompt': r'(.*)',
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'negative_prompt': r'Negative prompt: (.*)',
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'steps': r'Steps: (\d+),',
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'seed': r'Seed: (\d+),',
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'sampler': r'Sampler:\s*([^\s,]+(?:\s+[^\s,]+)*)',
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'model': r'Model:\s*([^\s,]+)',
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'cfg_scale': r'CFG scale:\s*([\d\.]+)',
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'size': r'Size:\s*([0-9]+x[0-9]+)'
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}
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for key in ['prompt', 'negative_prompt', 'steps', 'seed', 'sampler', 'model', 'cfg_scale', 'size']:
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match = re.search(patterns[key], text)
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if match:
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results[key] = match.group(1)
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else:
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results[key] = None
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if results['size'] is not None:
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w, h = results['size'].split("x")
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results['w'] = w
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results['h'] = h
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else:
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results['w'] = None
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results['h'] = None
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return results
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def send_to_txt2img(image):
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result = {tabs: gr.Tabs.update(selected="t2i")}
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try:
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text = image.info['parameters']
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data = get_data(text)
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result[prompt] = gr.update(value=data['prompt'])
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result[negative_prompt] = gr.update(value=data['negative_prompt']) if data['negative_prompt'] is not None else gr.update()
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result[steps] = gr.update(value=int(data['steps'])) if data['steps'] is not None else gr.update()
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result[seed] = gr.update(value=int(data['seed'])) if data['seed'] is not None else gr.update()
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result[cfg_scale] = gr.update(value=float(data['cfg_scale'])) if data['cfg_scale'] is not None else gr.update()
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result[width] = gr.update(value=int(data['w'])) if data['w'] is not None else gr.update()
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result[height] = gr.update(value=int(data['h'])) if data['h'] is not None else gr.update()
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result[sampler] = gr.update(value=data['sampler']) if data['sampler'] is not None else gr.update()
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if model in model_names:
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result[model] = gr.update(value=model_names[model])
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else:
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result[model] = gr.update()
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return result
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except Exception as e:
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print(e)
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result[prompt] = gr.update()
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result[negative_prompt] = gr.update()
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result[steps] = gr.update()
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result[seed] = gr.update()
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result[cfg_scale] = gr.update()
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result[width] = gr.update()
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result[height] = gr.update()
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result[sampler] = gr.update()
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result[model] = gr.update()
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return result
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prodia_client = Prodia(api_key=os.getenv("PRODIA_API_KEY"))
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model_list = prodia_client.list_models()
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model_names = {}
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for model_name in model_list:
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name_without_ext = remove_id_and_ext(model_name)
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model_names[name_without_ext] = model_name
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def flip_text(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):
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result = prodia_client.generate({
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with gr.Blocks(css=css) as demo:
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with gr.Row():
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with gr.Column(scale=6):
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model = gr.Dropdown(interactive=True,value="absolutereality_v181.safetensors [3d9d4d2b]", show_label=True, label="Stable Diffusion Checkpoint", choices=prodia_client.list_models())
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with gr.Column(scale=1):
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gr.Markdown(elem_id="powered-by-prodia", value="AUTOMATIC1111 Stable Diffusion Web UI.<br>Powered by [Prodia](https://prodia.com).<br> For more features and faster gen times check out our [API Docs](https://docs.prodia.com/reference/getting-started-guide)")
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with gr.Tabs() as tabs:
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with gr.Tab("txt2img", id='t2i'):
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with gr.Row():
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with gr.Column(scale=6, min_width=600):
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prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
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negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="3d, cartoon, anime, (deformed eyes, nose, ears, nose), bad anatomy, ugly")
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with gr.Column():
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text_button = gr.Button("Generate", variant='primary', elem_id="generate")
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with gr.Row():
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with gr.Column(scale=3):
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with gr.Tab("Generation"):
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with gr.Row():
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with gr.Column(scale=1):
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sampler = gr.Dropdown(value="Euler a", show_label=True, label="Sampling Method", choices=[
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"Euler",
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"Euler a",
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"LMS",
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"Heun",
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"DPM2",
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"DPM2 a",
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"DPM++ 2S a",
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"DPM++ 2M",
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"DPM++ SDE",
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"DPM fast",
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"DPM adaptive",
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"LMS Karras",
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"DPM2 Karras",
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"DPM2 a Karras",
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"DPM++ 2S a Karras",
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"DPM++ 2M Karras",
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"DPM++ SDE Karras",
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"DDIM",
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"PLMS",
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])
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with gr.Column(scale=1):
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steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)
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with gr.Row():
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with gr.Column(scale=1):
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width = gr.Slider(label="Width", maximum=1024, value=512, step=8)
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height = gr.Slider(label="Height", maximum=1024, value=512, step=8)
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with gr.Column(scale=1):
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batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
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batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
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cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
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seed = gr.Number(label="Seed", value=-1)
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with gr.Column(scale=2):
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image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
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text_button.click(flip_text, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)
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with gr.Tab("PNG Info"):
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def plaintext_to_html(text, classname=None):
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content = "<br>\n".join(html.escape(x) for x in text.split('\n'))
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return f"<p class='{classname}'>{content}</p>" if classname else f"<p>{content}</p>"
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def get_exif_data(image):
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items = image.info
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info = ''
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for key, text in items.items():
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info += f"""
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<div>
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<p><b>{plaintext_to_html(str(key))}</b></p>
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<p>{plaintext_to_html(str(text))}</p>
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</div>
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""".strip()+"\n"
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if len(info) == 0:
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message = "Nothing found in the image."
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info = f"<div><p>{message}<p></div>"
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return info
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with gr.Row():
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with gr.Column():
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image_input = gr.Image(type="pil")
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with gr.Column():
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exif_output = gr.HTML(label="EXIF Data")
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send_to_txt2img_btn = gr.Button("Send to txt2img")
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image_input.upload(get_exif_data, inputs=[image_input], outputs=exif_output)
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send_to_txt2img_btn.click(send_to_txt2img, inputs=[image_input], outputs=[tabs, prompt, negative_prompt, steps, seed,
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model, sampler, width, height, cfg_scale])
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demo.queue(concurrency_count=32)
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demo.launch()
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