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import os | |
import gradio as gr | |
from inference import load_models, cache_path | |
from PIL import Image | |
from os import path | |
canvas_size = 512 | |
if not path.exists(cache_path): | |
os.makedirs(cache_path, exist_ok=True) | |
with gr.Blocks() as demo: | |
infer = load_models() | |
with gr.Column(): | |
with gr.Row(): | |
with gr.Column(): | |
s = gr.Slider(label="steps", minimum=4, maximum=8, step=1, value=4, interactive=True) | |
c = gr.Slider(label="cfg", minimum=0.1, maximum=3, step=0.1, value=1, interactive=True) | |
i_s = gr.Slider(label="sketch strength", minimum=0.1, maximum=0.9, step=0.1, value=0.9, interactive=True) | |
with gr.Column(): | |
mod = gr.Text(label="Model HuggingFace id (after changing this wait until the model downloads in the console)", value="Lykon/dreamshaper-7", interactive=True) | |
t = gr.Text(label="Prompt", value="Scary warewolf, 8K, realistic, colorful, long sharp teeth, splash art", interactive=True) | |
se = gr.Number(label="seed", value=1337, interactive=True) | |
with gr.Row(equal_height=True): | |
i = gr.Image(source="canvas", tool="color-sketch", shape=(canvas_size, canvas_size), width=canvas_size, height=canvas_size, type="pil") | |
o = gr.Image(width=canvas_size, height=canvas_size) | |
def process_image(p, im, steps, cfg, image_strength, seed): | |
if not im: | |
return Image.new("RGB", (canvas_size, canvas_size)) | |
return infer( | |
prompt=p, | |
image=im, | |
num_inference_steps=steps, | |
guidance_scale=cfg, | |
strength=image_strength, | |
seed=int(seed) | |
) | |
reactive_controls = [t, i, s, c, i_s, se] | |
for control in reactive_controls: | |
control.change(fn=process_image, inputs=reactive_controls, outputs=o) | |
def update_model(model_name): | |
global infer | |
infer = load_models(model_name) | |
mod.change(fn=update_model, inputs=mod) | |
if __name__ == "__main__": | |
demo.launch() | |