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import gradio as gr
import sys
sys.path.append(".")
sys.path.append("..")
from model_loader import Model
from PIL import Image
import cv2
import io
from huggingface_hub import snapshot_download
models_path = snapshot_download(repo_id="radames/UserControllableLT", repo_type="model")
# models fron pretrained/latent_transformer folder
models_files = {
"anime": "anime.pt",
"car": "car.pt",
"cat": "cat.pt",
"church": "church.pt",
"ffhq": "ffhq.pt",
}
models = {name: Model(models_path + "/" + path) for name, path in models_files.items()}
canvas_html = """<draggan-canvas id="canvas-root" style='display:flex;max-width: 500px;margin: 0 auto;'></draggan-canvas>"""
load_js = """
async () => {
const script = document.createElement('script');
script.type = "module"
script.src = "file=custom_component.js"
document.head.appendChild(script);
}
"""
image_change = """
async (img) => {
const canvasEl = document.getElementById("canvas-root");
canvasEl.loadBase64Image(img);
}
"""
def cv_to_pil(img):
return Image.fromarray(cv2.cvtColor(img.astype("uint8"), cv2.COLOR_BGR2RGB))
def random_sample(model_name: str):
model = models[model_name]
img, latents = model.random_sample()
pil_img = cv_to_pil(img)
return pil_img, model_name, latents
def transform(model_state, latents_state, dxdysxsy="0,0,128,128", dz=0):
dx, dy, sx, sy = [
int(float(x)) if x.strip() != "" else 0 for x in dxdysxsy.split(",")
]
print(dx, dy, sx, sy)
model = models[model_state]
dx = dx
dy = dy
dz = dz
sx = sx
sy = sy
stop_points = []
img, latents_state = model.transform(
latents_state, dz, dxy=[dx, dy], sxsy=[sx, sy], stop_points=stop_points
)
pil_img = cv_to_pil(img)
return pil_img, latents_state
def change_style(image: Image.Image, model_state, latents_state):
model = models[model_state]
img, latents_state = model.change_style(latents_state)
pil_img = cv_to_pil(img)
return pil_img, latents_state
def reset(model_state, latents_state):
model = models[model_state]
img, latents_state = model.reset(latents_state)
pil_img = cv_to_pil(img)
return pil_img, latents_state
def image_click(evt: gr.SelectData):
click_pos = evt.index
return click_pos
with gr.Blocks() as block:
model_state = gr.State(value="cat")
latents_state = gr.State({})
gr.Markdown("# UserControllableLT: User controllable latent transformer")
gr.Markdown("## Select model")
with gr.Row():
with gr.Column():
model_name = gr.Dropdown(
choices=list(models_files.keys()),
label="Select Pretrained Model",
value="cat",
)
with gr.Row():
button = gr.Button("Random sample")
reset_btn = gr.Button("Reset")
change_style_bt = gr.Button("Change style")
dxdysxsy = gr.Textbox(label="dxdysxsy", value="0,0,128,128", elem_id="dxdysxsy" ,visible=False)
dz = gr.Slider(minimum=-5, maximum=5, step_size=0.01, label="zoom", value=0.0)
image = gr.Image(type="pil", visible=False)
with gr.Column():
html = gr.HTML(canvas_html, label="output")
button.click(
random_sample, inputs=[model_name], outputs=[image, model_state, latents_state]
)
reset_btn.click(
reset,
inputs=[model_state, latents_state],
outputs=[image, latents_state],
)
change_style_bt.click(
change_style,
inputs=[image, model_state, latents_state],
outputs=[image, latents_state],
)
dxdysxsy.change(
transform,
inputs=[model_state, latents_state, dxdysxsy, dz],
outputs=[image, latents_state],
show_progress=False,
)
dz.change(
transform,
inputs=[model_state, latents_state, dxdysxsy, dz],
outputs=[image, latents_state],
show_progress=False,
)
image.change(None, inputs=[image], outputs=None, _js=image_change)
block.load(None, None, None, _js=load_js)
block.load(random_sample, inputs=[model_name], outputs=[image, model_state, latents_state])
block.queue()
block.launch()
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