|
|
|
|
|
from __future__ import annotations |
|
|
|
import json |
|
|
|
import gradio as gr |
|
import numpy as np |
|
|
|
from model import Model |
|
|
|
DESCRIPTION = "# [StyleGAN2](https://github.com/NVlabs/stylegan3)" |
|
|
|
|
|
def update_class_index(name: str) -> dict: |
|
if name == "CIFAR-10": |
|
return gr.Slider(maximum=9, visible=True) |
|
else: |
|
return gr.Slider(visible=False) |
|
|
|
|
|
def get_sample_image_url(name: str) -> str: |
|
sample_image_dir = "https://huggingface.co./spaces/hysts/StyleGAN2/resolve/main/samples" |
|
return f"{sample_image_dir}/{name}.jpg" |
|
|
|
|
|
def get_sample_image_markdown(name: str) -> str: |
|
url = get_sample_image_url(name) |
|
if name == "cifar10": |
|
size = 32 |
|
class_index = "0-9" |
|
seed = "0-9" |
|
else: |
|
class_index = "N/A" |
|
seed = "0-99" |
|
if name == "afhq-cat": |
|
size = 512 |
|
elif name == "afhq-dog": |
|
size = 512 |
|
elif name == "afhq-wild": |
|
size = 512 |
|
elif name == "afhqv2": |
|
size = 512 |
|
elif name == "brecahad": |
|
size = 256 |
|
elif name == "celebahq": |
|
size = 1024 |
|
elif name == "ffhq": |
|
size = 1024 |
|
elif name == "ffhq-u": |
|
size = 1024 |
|
elif name == "lsun-dog": |
|
size = 256 |
|
elif name == "metfaces": |
|
size = 1024 |
|
elif name == "metfaces-u": |
|
size = 1024 |
|
else: |
|
raise ValueError |
|
|
|
return f""" |
|
- size: {size}x{size} |
|
- class_index: {class_index} |
|
- seed: {seed} |
|
- truncation: 0.7 |
|
![sample images]({url})""" |
|
|
|
|
|
def load_class_names(name: str) -> list[str]: |
|
with open(f"labels/{name}_classes.json") as f: |
|
names = json.load(f) |
|
return names |
|
|
|
|
|
def get_class_name_df(name: str) -> list: |
|
names = load_class_names(name) |
|
return list(map(list, enumerate(names))) |
|
|
|
|
|
CIFAR10_NAMES = load_class_names("cifar10") |
|
|
|
|
|
def update_class_name(model_name: str, index: int) -> dict: |
|
if model_name == "CIFAR-10": |
|
value = CIFAR10_NAMES[index] |
|
return gr.Textbox(value=value, visible=True) |
|
else: |
|
return gr.Textbox(visible=False) |
|
|
|
|
|
model = Model() |
|
|
|
with gr.Blocks(css="style.css") as demo: |
|
gr.Markdown(DESCRIPTION) |
|
|
|
with gr.Tabs(): |
|
with gr.TabItem("App"): |
|
with gr.Row(): |
|
with gr.Column(): |
|
model_name = gr.Dropdown( |
|
label="Model", choices=list(model.MODEL_NAME_DICT.keys()), value="FFHQ-1024" |
|
) |
|
seed = gr.Slider(label="Seed", minimum=0, maximum=np.iinfo(np.uint32).max, step=1, value=0) |
|
psi = gr.Slider(label="Truncation psi", minimum=0, maximum=2, step=0.05, value=0.7) |
|
class_index = gr.Slider(label="Class Index", minimum=0, maximum=9, step=1, value=0, visible=False) |
|
class_name = gr.Textbox( |
|
label="Class Label", value=CIFAR10_NAMES[class_index.value], interactive=False, visible=False |
|
) |
|
run_button = gr.Button() |
|
with gr.Column(): |
|
result = gr.Image(label="Result") |
|
|
|
with gr.TabItem("Sample Images"): |
|
with gr.Row(): |
|
model_name2 = gr.Dropdown( |
|
label="Model", |
|
choices=[ |
|
"afhq-cat", |
|
"afhq-dog", |
|
"afhq-wild", |
|
"afhqv2", |
|
"brecahad", |
|
"celebahq", |
|
"cifar10", |
|
"ffhq", |
|
"ffhq-u", |
|
"lsun-dog", |
|
"metfaces", |
|
"metfaces-u", |
|
], |
|
value="afhq-cat", |
|
) |
|
with gr.Row(): |
|
text = get_sample_image_markdown(model_name2.value) |
|
sample_images = gr.Markdown(text) |
|
|
|
model_name.change( |
|
fn=update_class_index, |
|
inputs=model_name, |
|
outputs=class_index, |
|
queue=False, |
|
api_name=False, |
|
) |
|
model_name.change( |
|
fn=update_class_name, |
|
inputs=[ |
|
model_name, |
|
class_index, |
|
], |
|
outputs=class_name, |
|
queue=False, |
|
api_name=False, |
|
) |
|
class_index.change( |
|
fn=update_class_name, |
|
inputs=[ |
|
model_name, |
|
class_index, |
|
], |
|
outputs=class_name, |
|
queue=False, |
|
api_name=False, |
|
) |
|
run_button.click( |
|
fn=model.set_model_and_generate_image, |
|
inputs=[ |
|
model_name, |
|
seed, |
|
psi, |
|
class_index, |
|
], |
|
outputs=result, |
|
api_name="run", |
|
) |
|
model_name2.change( |
|
fn=get_sample_image_markdown, |
|
inputs=model_name2, |
|
outputs=sample_images, |
|
queue=False, |
|
api_name=False, |
|
) |
|
|
|
if __name__ == "__main__": |
|
demo.queue(max_size=10).launch() |
|
|