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import os
import shutil
import torch
import cv2
import gradio as gr
from PIL import Image
# Download sample images
os.makedirs("sample_images", exist_ok=True)
os.chdir("sample_images")
os.system("gdown 1LiKfKhksfu8f_A4x-BhOjZgZHADdLdWz -O img1.jpg")
os.system("gdown 1jJ6uP_bpdnCRqCuiqZjJG8yeexsz6IUp -O img2.jpg")
os.system("gdown 1usp9c4VcTX2yche5o2WCi7yJw85n_yeZ -O img3.jpg")
os.chdir("../")
examples = [['sample_images/img1.jpg', "Cartoonify"],
['sample_images/img2.jpg', "Cartoonify"],
['sample_images/img3.jpg', "Cartoonify"],
]
inference_on = ['Full Resolution Image', 'Downsampled Image']
title = "Face Cartoonify for Video Call Privacy"
description = """
Gradio demo for <b>Face Cartoonify for Video Call Privacy</b>.\n
"""
article = "<p style='text-align: center'><a href='#'> Face Cartoonify for Video Call Privacy </a> | <a href='#'>Github Repo</a></p>"
model = torch.hub.load(
"AK391/animegan2-pytorch:main",
"generator",
pretrained=True,
device="cpu",
progress=False
)
face2paint = torch.hub.load(
'AK391/animegan2-pytorch:main', 'face2paint',
size=512, device="cpu",side_by_side=False
)
def inference(img, method):
if not os.path.exists('temp'):
os.system('mkdir temp')
img.save("temp/image.jpg", "JPEG")
if method == "Cartoonify AnimeGanV2":
out = face2paint(model, img)
return out
else:
os.system("python cartoon.py --input_path 'temp/image.jpg' --result_dir './temp/'")
return 'temp/image.jpg'
gr.Interface(
inference,
[
gr.inputs.Image(type="pil", label="Input"),
gr.inputs.Radio(["Cartoonify OpenCV", "Cartoonify AnimeGanV2"], default="Cartoonify AnimeGanV2", label='Method'),
],
gr.outputs.Image(type="file", label="Output"),
title=title,
description=description,
article=article,
theme ="huggingface",
examples=examples,
allow_flagging=False,
).launch(debug=True,enable_queue=True)
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