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import os | |
os.system("pip install gradio==3.50") | |
import gradio as gr | |
from PIL import Image | |
import subprocess | |
# Install necessary packages | |
os.system("pip install 'git+https://github.com/facebookresearch/detectron2.git'") | |
# Clone the repository | |
os.system("git clone https://github.com/ShuhongChen/bizarre-pose-estimator.git") | |
os.chdir("bizarre-pose-estimator") | |
# Download necessary files | |
os.system("wget https://i.imgur.com/IkJzlaE.jpeg") | |
os.system("gdown https://drive.google.com/uc?id=17N5PutpYJTlKuNB6bdDaiQsPSIkYtiPm") | |
# Unzip and move the model files | |
os.system("unzip bizarre_pose_models.zip") | |
os.system("cp -a ./bizarre_pose_models/. .") | |
def inference(img): | |
# Save the input image | |
img.save("_input.png") | |
# Run the pose estimator | |
os.system("python3 -m _scripts.pose_estimator _input.png ./_train/character_pose_estim/runs/feat_concat+data.ckpt") | |
# Load and return the output image | |
return Image.open("./_samples/character_pose_estim.png") | |
title = "bizarre-pose-estimator" | |
description = "Gradio demo for Transfer Learning for Pose Estimation of Illustrated Characters. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below." | |
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2108.01819' target='_blank'>Transfer Learning for Pose Estimation of Illustrated Characters</a> | <a href='https://github.com/ShuhongChen/bizarre-pose-estimator' target='_blank'>Github Repo</a></p>" | |
examples=[["IkJzlaE.jpeg"]] | |
gr.Interface( | |
inference, | |
gr.inputs.Image(type="file", label="Input"), | |
gr.outputs.Image(type="file", label="Output"), | |
title=title, | |
description=description, | |
article=article, | |
allow_flagging="never", | |
examples=examples, | |
enable_queue=True | |
).launch() | |