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montyanderson
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d6c5ef7
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Parent(s):
2af6f8e
Revert "Batch count functionality + stop btn (#15)"
Browse filesThis reverts commit 2af6f8ecf76dbdea6c320bfd1b37b582368355a0.
app.py
CHANGED
@@ -7,11 +7,9 @@ import base64
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import os
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from io import BytesIO
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import PIL
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from PIL import Image
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from PIL.ExifTags import TAGS
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import html
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import re
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from threading import Thread
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class Prodia:
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@@ -161,8 +159,8 @@ 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 txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed,
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"prompt": prompt,
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"negative_prompt": negative_prompt,
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"model": model,
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@@ -172,35 +170,17 @@ def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, he
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"width": width,
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"height": height,
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"seed": seed
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}
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threads = []
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def generate_one_image():
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result = prodia_client.generate(data)
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job = prodia_client.wait(result)
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total_images.append(job['imageUrl'])
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for x in range(batch_count):
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t = Thread(target=generate_one_image)
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threads.append(t)
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t.start()
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for t in threads:
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t.join()
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new_images_list = [img['name'] for img in gallery]
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new_images_list.insert(0, image)
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def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed,
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batch_count, gallery):
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data = {
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"imageData": image_to_base64(input_image),
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"denoising_strength": denoising,
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"prompt": prompt,
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@@ -212,30 +192,21 @@ def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampl
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"width": width,
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"height": height,
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"seed": seed
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}
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total_images = []
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threads = []
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result = prodia_client.transform(data)
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job = prodia_client.wait(result)
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total_images.append(job['imageUrl'])
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for x in range(batch_count):
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t = Thread(target=generate_one_image)
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threads.append(t)
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t.start()
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for t in threads:
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t.join()
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new_images_list = [img['name'] for img in gallery]
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for image in total_images:
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new_images_list.insert(0, image)
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samplers = [
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"Euler",
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@@ -259,7 +230,7 @@ samplers = [
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"PLMS",
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]
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with gr.Blocks() 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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@@ -274,9 +245,8 @@ with gr.Blocks() as demo:
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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.
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text_button = gr.Button("Generate", variant='primary')
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stop_btn = gr.Button("Cancel", elem_id="cancel")
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with gr.Row():
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with gr.Column(scale=3):
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@@ -315,14 +285,14 @@ with gr.Blocks() as demo:
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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",
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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.
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with gr.Tab("img2img", id='i2i'):
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@@ -330,9 +300,8 @@ with gr.Blocks() as demo:
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with gr.Column(scale=6, min_width=600):
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i2i_prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
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i2i_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.
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i2i_text_button = gr.Button("Generate", variant='primary', elem_id="generate")
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i2i_stop_btn = gr.Button("Cancel", elem_id="cancel")
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with gr.Row():
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with gr.Column(scale=3):
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@@ -353,7 +322,7 @@ with gr.Blocks() as demo:
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with gr.Column(scale=1):
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i2i_batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
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i2i_batch_count = gr.Slider(label="Batch Count",
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i2i_cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
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i2i_denoising = gr.Slider(label="Denoising Strength", minimum=0, maximum=1, value=0.7, step=0.1)
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@@ -361,7 +330,7 @@ with gr.Blocks() as demo:
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with gr.Column(scale=2):
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i2i_image_output = gr.
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with gr.Tab("PNG Info"):
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@@ -400,15 +369,12 @@ with gr.Blocks() as demo:
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with gr.Tab("Gallery"):
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gallery_obj = gr.Gallery(height=500, columns=4)
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stop_btn.click(fn=None, outputs=None, cancels=[t2i_event])
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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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i2i_event = i2i_text_button.click(img2img, inputs=[i2i_image_input, i2i_denoising, i2i_prompt, i2i_negative_prompt, model, i2i_steps, i2i_sampler, i2i_cfg_scale, i2i_width, i2i_height, i2i_seed, i2i_batch_count, gallery_obj], outputs=[i2i_image_output, gallery_obj])
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i2i_stop_btn.click(fn=None, outputs=None, cancels=[i2i_event])
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demo.queue(concurrency_count=32)
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demo.launch()
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import os
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from io import BytesIO
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import PIL
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from PIL.ExifTags import TAGS
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import html
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import re
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class Prodia:
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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 txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed, gallery):
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result = prodia_client.generate({
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"prompt": prompt,
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"negative_prompt": negative_prompt,
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"model": model,
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"width": width,
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"height": height,
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"seed": seed
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})
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job = prodia_client.wait(result)
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new_images_list = [img['name'] for img in gallery]
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new_images_list.insert(0, job["imageUrl"])
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return {image_output: job["imageUrl"], gallery_obj: new_images_list}
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def img2img(input_image, denoising, prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed, gallery):
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result = prodia_client.transform({
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"imageData": image_to_base64(input_image),
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"denoising_strength": denoising,
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"prompt": prompt,
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"width": width,
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"height": height,
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"seed": seed
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})
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job = prodia_client.wait(result)
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new_images_list = [img['name'] for img in gallery]
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new_images_list.insert(0, job["imageUrl"])
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return {i2i_image_output: job["imageUrl"], gallery_obj: new_images_list}
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css = """
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#generate {
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height: 100%;
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}
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"""
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samplers = [
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"Euler",
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"PLMS",
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]
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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=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.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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with gr.Tab("img2img", id='i2i'):
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with gr.Column(scale=6, min_width=600):
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i2i_prompt = gr.Textbox("space warrior, beautiful, female, ultrarealistic, soft lighting, 8k", placeholder="Prompt", show_label=False, lines=3)
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i2i_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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i2i_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.Column(scale=1):
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i2i_batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)
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i2i_batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)
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i2i_cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)
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i2i_denoising = gr.Slider(label="Denoising Strength", minimum=0, maximum=1, value=0.7, step=0.1)
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with gr.Column(scale=2):
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i2i_image_output = gr.Image(value="https://images.prodia.xyz/8ede1a7c-c0ee-4ded-987d-6ffed35fc477.png")
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with gr.Tab("PNG Info"):
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with gr.Tab("Gallery"):
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gallery_obj = gr.Gallery(height=500, columns=4)
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text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed, gallery_obj], outputs=[image_output, gallery_obj])
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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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i2i_text_button.click(img2img, inputs=[i2i_image_input, i2i_denoising, i2i_prompt, i2i_negative_prompt, model, i2i_steps, i2i_sampler, i2i_cfg_scale, i2i_width, i2i_height, i2i_seed, gallery_obj], outputs=[i2i_image_output, gallery_obj])
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demo.queue(concurrency_count=32)
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demo.launch()
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