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from pydoc import describe
from huggingface_hub import hf_hub_download
import gradio as gr
import subprocess
import os
import datetime
from PIL import Image
from remove_bg import RemoveBackground
net_C = hf_hub_download("radames/PIFu-upright-standing", filename="net_C")
net_G = hf_hub_download("radames/PIFu-upright-standing", filename="net_G")
remove_bg = RemoveBackground()
env = {
**os.environ,
"CHECKPOINTS_NETG_PATH": net_G,
"CHECKPOINTS_NETC_PATH": net_C,
"RESULTS_PATH": './results',
}
def process(img_path, resolution=128):
base = os.path.basename(img_path)
img_name = os.path.splitext(base)[0]
print("image name", img_name)
img = Image.open(img_path)
# remove background
print("remove background")
foreground = Image.fromarray(remove_bg.inference(img), 'RGBA')
foreground.save("./PIFu/inputs/" + img_name + ".png")
print("align mask with input training image")
subprocess.Popen(["python", "./apps/crop_img.py", "--input_image",
f'./inputs/{img_name}.png', "--out_path", "./inputs"], cwd="PIFu").communicate()
print("generate 3D model")
subprocess.Popen("./scripts/test.sh", env={
**env,
"INPUT_IMAGE_PATH": f'./inputs/{img_name}.png',
"VOL_RES": "256"},
cwd="PIFu").communicate()
print("inference")
return f'./PIFu/results/spaces_demo/result_{img_name}.glb'
examples = [["./examples/" + img] for img in os.listdir("./examples/")]
description = '''
### PIFu-upright-standing
Credits
https://stylegan-human.github.io/
https://phorhum.github.io/
https://github.com/yuliangxiu/icon
https://shunsukesaito.github.io/PIFuHD/
'''
iface = gr.Interface(
fn=process,
description=description,
inputs=gr.Image(type="filepath", label="Input"),
outputs=gr.Model3D(clear_color=[0.0, 0.0, 0.0, 0.0]),
examples=examples,
allow_flagging="never",
cache_examples=True
)
if __name__ == "__main__":
iface.launch(debug=True, enable_queue=False)
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