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import os | |
import shutil | |
import subprocess | |
import textwrap | |
from pathlib import Path | |
import gradio as gr | |
import torch | |
from huggingface_hub import hf_hub_download | |
REPO_ID = "kbrodt/sketch2pose" | |
API_TOKEN = os.environ["sketch2pose"] | |
ASSET_DIR = Path("./assets") | |
SAVE_DIR = "output" | |
CMD = textwrap.dedent(""" | |
python src/pose.py | |
--save-path {} | |
--img-path {} | |
""") | |
TITLE = "Sketch2Pose: Estimating a 3D Character Pose from a Bitmap Sketch" | |
DESCRIPTION = ''' | |
<table> | |
<th> | |
<ul> | |
<li> | |
<a href="http://www-labs.iro.umontreal.ca/~bmpix/sketch2pose/">project page</a> | |
</li> | |
<li> | |
<a href="https://github.com/kbrodt/sketch2pose">code</a> | |
<iframe src="https://ghbtns.com/github-btn.html?user=kbrodt&repo=sketch2pose&type=star&count=true&v=2&size=small" frameborder="0" scrolling="0" width="100" height="20"></iframe> | |
</li> | |
<li> | |
<a href="https://dl.acm.org/doi/10.1145/3528223.3530106">paper ACM SIGGRAPH 2022</a> | |
</li> | |
</ul> | |
</th> | |
<th> | |
<video width="560" height="315" controls autoplay muted loop> | |
<source src="http://www-labs.iro.umontreal.ca/~bmpix/sketch2pose/sketch2pose.webm" type="video/mp4"> | |
</video> | |
</th> | |
</table> | |
''' | |
def prepare(): | |
filename = "models_smplx_v1_1.zip" | |
smpl_path = hf_hub_download( | |
repo_id=REPO_ID, | |
repo_type="model", | |
filename=filename, | |
use_auth_token=API_TOKEN, | |
cache_dir=ASSET_DIR, | |
) | |
if not (ASSET_DIR / filename).is_file(): | |
shutil.copy(smpl_path, ASSET_DIR) | |
subprocess.run("bash ./scripts/download.sh".split()) | |
subprocess.run("bash ./scripts/prepare.sh".split()) | |
def main(): | |
prepare() | |
save_dir = Path(SAVE_DIR) | |
save_dir.mkdir(parents=True, exist_ok=True) | |
def pose(img_path, use_cos=True, use_angle_transf=True, use_contacts=False, use_natural=True): | |
if use_cos == False: | |
use_angle_transf = False | |
cmd = CMD.format(save_dir, img_path) | |
if use_cos: | |
cmd = cmd + " --use-cos" | |
if use_angle_transf: | |
cmd = cmd + " --use-angle-transf" | |
if use_contacts: | |
cmd = cmd + " --use-contacts" | |
if use_natural: | |
cmd = cmd + " --use-natural" | |
out_dir = (save_dir / Path(img_path).name).with_suffix("") | |
mesh_path = out_dir / "us.glb" | |
if not mesh_path.is_file(): | |
subprocess.call(cmd.split()) | |
return str(mesh_path) | |
examples = [] | |
for img_path in Path("./data/images").glob("*"): | |
examples.append([str(img_path), True, True, False, True]) | |
break | |
demo = gr.Interface( | |
fn=pose, | |
inputs=[ | |
gr.Image(type="filepath", label="Image"), | |
gr.Checkbox(value=True, label="Bone lenghts"), | |
gr.Checkbox(value=True, label="Foreshortening"), | |
gr.Checkbox(value=False, label="Self-contacts (available with cuda)", interactive=torch.cuda.is_available()), | |
gr.Checkbox(value=True, label="Pose naturalness"), | |
], | |
outputs=gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0], label="SMPL 3D pose"), | |
examples=examples, | |
title=TITLE, | |
description=DESCRIPTION, | |
) | |
demo.launch() | |
if __name__ == "__main__": | |
main() | |