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import gradio as gr | |
from fetch import get_values | |
from dotenv import load_dotenv | |
load_dotenv() | |
import prodia | |
import requests | |
import random | |
from datetime import datetime | |
import os | |
prodia_key = os.getenv('PRODIA_X_KEY', None) | |
if prodia_key is None: | |
print("Please set PRODIA_X_KEY in .env, closing...") | |
exit() | |
client = prodia.Client(api_key=prodia_key) | |
def process_input_text2img(prompt, negative_prompt, steps, cfg_scale, number, seed, model, sampler, aspect_ratio, upscale, save=False): | |
images = [] | |
for image in range(number): | |
result = client.sd_generate(prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, | |
steps=steps, cfg_scale=cfg_scale, seed=seed, aspect_ratio=aspect_ratio, upscale=upscale) | |
images.append(result.url) | |
if save: | |
date = datetime.now() | |
if not os.path.isdir(f'./outputs/{date.year}-{date.month}-{date.day}'): | |
os.mkdir(f'./outputs/{date.year}-{date.month}-{date.day}') | |
img_data = requests.get(result.url).content | |
with open(f"./outputs/{date.year}-{date.month}-{date.day}/{random.randint(1, 10000000000000)}_{result.seed}.png", "wb") as f: | |
f.write(img_data) | |
return images | |
def process_input_img2img(init, prompt, negative_prompt, steps, cfg_scale, number, seed, model, sampler, ds, upscale, save): | |
images = [] | |
for image in range(number): | |
result = client.sd_transform(imageUrl=init, prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, | |
steps=steps, cfg_scale=cfg_scale, seed=seed, denoising_strength=ds, upscale=upscale) | |
images.append(result.url) | |
if save: | |
date = datetime.now() | |
if not os.path.isdir(f'./outputs/{date.year}-{date.month}-{date.day}'): | |
os.mkdir(f'./outputs/{date.year}-{date.month}-{date.day}') | |
img_data = requests.get(result.url).content | |
with open(f"./outputs/{date.year}-{date.month}-{date.day}/{random.randint(1, 10000000000000)}_{result.seed}.png", "wb") as f: | |
f.write(img_data) | |
return images | |
""" | |
def process_input_control(init, prompt, negative_prompt, steps, cfg_scale, number, seed, model, control_model, sampler): | |
images = [] | |
for image in range(number): | |
result = client.controlnet(imageUrl=init, prompt=prompt, negative_prompt=negative_prompt, model=model, sampler=sampler, | |
steps=steps, cfg_scale=cfg_scale, seed=seed, controlnet_model=control_model) | |
images.append(result.url) | |
return images | |
""" | |
theme = gr.themes.Base( | |
primary_hue=gr.themes.Color(c100="#dbeafe", c200="#bfdbfe", c300="#93c5fd", c400="#60a5fa", c50="#eff6ff", c500="#3b82f6", c600="#2563eb", c700="#fb3657", c800="#1e40af", c900="#1e3a8a", c950="#1d3660"), | |
neutral_hue=gr.themes.Color(c100="#e0e7ff", c200="#c7d2fe", c300="#3c4367", c400="#b5b5b5", c50="#eef2ff", c500="#757575", c600="#221935", c700="#09001b", c800="#0f0e27", c900="#0f0e27", c950="#09001b"), | |
).set( | |
block_background_fill='*background_fill_secondary' | |
) | |
with gr.Blocks(theme=theme) as demo: | |
gr.Markdown(""" | |
# Prodia API web-ui by @zenafey | |
This is simple web-gui for using Prodia API easily, build on Python, gradio, prodiapy | |
""") | |
with gr.Tab(label="text2img"): | |
with gr.Row(): | |
with gr.Column(): | |
prompt = gr.Textbox(label="Prompt", lines=2, placeholder="puppies in a cloud, 4k") | |
negative = gr.Textbox(label="Negative Prompt", lines=3, placeholder="Add words you don't want to show up in your art...") | |
with gr.Row(): | |
steps = gr.Slider(label="Steps", value=30, step=1, maximum=50, minimum=1, interactive=True) | |
cfg = gr.Slider(label="CFG Scale", maximum=20, minimum=1, value=7, interactive=True) | |
with gr.Row(): | |
num = gr.Slider(label="Number of images", value=1, step=1, minimum=1, interactive=True) | |
seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=4294967295, interactive=True) | |
with gr.Row(): | |
model = gr.Dropdown(label="Model", choices=get_values()[0], value="v1-5-pruned-emaonly.ckpt [81761151]", interactive=True) | |
sampler = gr.Dropdown(label="Sampler", choices=get_values()[1], value="DDIM", interactive=True) | |
with gr.Row(): | |
ar = gr.Radio(label="Aspect Ratio", choices=["square", "portrait", "landscape"], value="square", interactive=True) | |
with gr.Column(): | |
upscale = gr.Checkbox(label="upscale", interactive=True) | |
with gr.Row(): | |
run_btn = gr.Button("Run", variant="primary") | |
with gr.Column(): | |
result_image = gr.Gallery(label="Result Image(s)") | |
run_btn.click( | |
process_input_text2img, | |
inputs=[ | |
prompt, | |
negative, | |
steps, | |
cfg, | |
num, | |
seed, | |
model, | |
sampler, | |
ar, | |
upscale | |
], | |
outputs=[result_image], | |
) | |
with gr.Tab(label="img2img"): | |
with gr.Row(): | |
with gr.Column(): | |
prompt = gr.Textbox(label="Prompt", lines=2, placeholder="puppies in a cloud, 4k") | |
with gr.Row(): | |
negative = gr.Textbox(label="Negative Prompt", lines=3, placeholder="Add words you don't want to show up in your art...") | |
init_image = gr.Textbox(label="Init Image Url", lines=2, placeholder="https://cdn.openai.com/API/images/guides/image_generation_simple.webp") | |
with gr.Row(): | |
steps = gr.Slider(label="Steps", value=30, step=1, maximum=50, minimum=1, interactive=True) | |
cfg = gr.Slider(label="CFG Scale", maximum=20, minimum=1, value=7, interactive=True) | |
with gr.Row(): | |
num = gr.Slider(label="Number of images", value=1, step=1, minimum=1, interactive=True) | |
seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=4294967295, interactive=True) | |
with gr.Row(): | |
model = gr.Dropdown(label="Model", choices=get_values()[0], value="v1-5-pruned-emaonly.ckpt [81761151]", interactive=True) | |
sampler = gr.Dropdown(label="Sampler", choices=get_values()[1], value="DDIM", interactive=True) | |
with gr.Row(): | |
ds = gr.Slider(label="Denoising strength", maximum=0.9, minimum=0.1, value=0.5, interactive=True) | |
with gr.Column(): | |
upscale = gr.Checkbox(label="upscale", interactive=True) | |
with gr.Row(): | |
run_btn = gr.Button("Run", variant="primary") | |
with gr.Column(): | |
result_image = gr.Gallery(label="Result Image(s)") | |
run_btn.click( | |
process_input_img2img, | |
inputs=[ | |
init_image, | |
prompt, | |
negative, | |
steps, | |
cfg, | |
num, | |
seed, | |
model, | |
sampler, | |
ds, | |
upscale | |
], | |
outputs=[result_image], | |
) | |
with gr.Tab(label="controlnet(coming soon)"): | |
gr.Button(label="lol") | |
if __name__ == "__main__": | |
demo.launch(show_api=True) | |