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import os
import numpy as np
from prodiapy import Prodia
import gradio as gr
import base64
prodia = Prodia()
STYLE_PRESETS = [None, "3d-model", "analog-film", "anime", "cinematic", "comic-book", "digital-art", "enhance", "fantasy-art", "isometric", "line-art", "low-poly",
"neon-punk", "origami", "photographic", "pixel-art", "texture", "craft-clay"]
MAX_SEED = np.iinfo(np.int32).max
def generate_image(upload_images, prompt, negative_prompt, style_preset, steps, strength, seed, progress=gr.Progress(track_tqdm=True)):
error_if_no_img(prompt)
job = prodia.create("/photomaker",
imageData=[file_to_base64(img) for img in upload_images],
prompt=prompt,
negative_prompt=negative_prompt,
style_preset=style_preset,
steps=steps,
strength=strength,
seed=seed if seed != 0 else None
)
result = prodia.wait(job)
return result.image_url
def error_if_no_img(prompt):
if "img" not in prompt:
raise gr.Error("Prompt must contain 'img'")
def swap_to_gallery(images):
return gr.update(value=images, visible=True), gr.update(visible=True), gr.update(visible=False)
def upload_example_to_gallery(images, prompt, style, negative_prompt):
return gr.update(value=images, visible=True), gr.update(visible=True), gr.update(visible=False)
def remove_back_to_files():
return gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
def get_image_path_list(folder_name):
image_basename_list = os.listdir(folder_name)
image_path_list = sorted([os.path.join(folder_name, basename) for basename in image_basename_list])
return image_path_list
def file_to_base64(file_path):
with open(file_path, "rb") as file:
file_data = file.read()
base64_string = base64.b64encode(file_data).decode('utf-8')
return base64_string
def get_example():
case = [
[
get_image_path_list('./examples/scarletthead_woman'),
"instagram photo, portrait photo of a woman img, colorful, perfect face, natural skin, hard shadows, film grain",
None,
"(asymmetry, worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
],
[
get_image_path_list('./examples/newton_man'),
"sci-fi, closeup portrait photo of a man img wearing the sunglasses in Iron man suit, face, slim body, high quality, film grain",
None,
"(asymmetry, worst quality, low quality, illustration, 3d, 2d, painting, cartoons, sketch), open mouth",
],
]
return case
title = r"""
<h1 align="center">PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding</h1>
"""
css = '''
.gradio-container {width: 85% !important}
'''
with gr.Blocks(css=css) as demo:
gr.Markdown(title)
with gr.Row():
with gr.Column():
files = gr.File(
label="Drag (Select) 1 or more photos of your face",
file_types=["image"],
file_count="multiple"
)
uploaded_files = gr.Gallery(label="Your images", visible=False, columns=5, rows=1, height=200)
with gr.Column(visible=False) as clear_button:
remove_and_reupload = gr.ClearButton(value="Remove and upload new ones", components=files, size="sm")
prompt = gr.Textbox(label="Prompt",
info="Try something like 'a photo of a man/woman img', 'img' is the trigger word.",
placeholder="A photo of a [man/woman img]...")
style = gr.Dropdown(label="Style template", choices=STYLE_PRESETS, value=None)
submit = gr.Button("Submit")
with gr.Accordion(open=False, label="Advanced Options"):
negative_prompt = gr.Textbox(
label="Negative Prompt",
placeholder="low quality",
value="nsfw, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry",
)
steps = gr.Slider(
label="Number of sample steps",
minimum=20,
maximum=50,
step=1,
value=40,
)
strength_ratio = gr.Slider(
label="Strength (%)",
minimum=15,
maximum=50,
step=1,
value=20,
)
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=0,
)
with gr.Column():
result_image = gr.Image(label="Generated Image")
files.upload(fn=swap_to_gallery, inputs=files, outputs=[uploaded_files, clear_button, files])
remove_and_reupload.click(fn=remove_back_to_files, outputs=[uploaded_files, clear_button, files])
submit.click(
fn=generate_image,
inputs=[files, prompt, negative_prompt, style, steps, strength_ratio, seed],
outputs=[result_image]
)
gr.Examples(
examples=get_example(),
inputs=[files, prompt, style, negative_prompt],
run_on_click=True,
fn=upload_example_to_gallery,
outputs=[uploaded_files, clear_button, files],
)
demo.queue(max_size=20).launch(show_api=False)
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