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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)
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