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import numpy as np
import gradio as gr
import cv2
import os
import argparse
from inference import Predictor
#from black import to_black
# os.system("wget https://huggingface.co/YANGYYYY/cartoonize/tree/main/GeneratorV2_train_photo_Hayao_init.pt")
# if os.path.exists("GeneratorV2_train_photo_Hayao_init.pt"):
# print("下载成功!")
# else:
# print("下载失败!")
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--weight', type=str, default='GeneratorV2_train_photo_Hayao_init.pt')
parser.add_argument('--device', type=str, default='cpu', help='Device, cuda or cpu')
return parser.parse_args()
def parse_args_video():
parser = argparse.ArgumentParser()
parser.add_argument('--weight', type=str, default='GeneratorV2_train_photo_Hayao_init.pt')
#parser.add_argument('--src', type=str, default='dataset/video/花.mp4', help='Path to input video')
#parser.add_argument('--out', type=str, default='dataset/video_Hayao/hua_hayao.mp4', help='Path to save new video')
parser.add_argument('--batch-size', type=int, default=4)
parser.add_argument('--start', type=int, default=0, help='Start time of video (second)')
parser.add_argument('--end', type=int, default=10, help='End time of video (second), 0 if not set')
return parser.parse_args()
def transfer(image, transfer_style):
if transfer_style == "Hayao":
#output = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)# 转换为灰度图像
#os.system("wget https://huggingface.co/YANGYYYY/cartoonize/resolve/main/GeneratorV2_train_photo_Hayao_init.pt")
args = parse_args()
predictor = Predictor(args.weight, args.device)
anime_img = predictor.transform_image(image)
return anime_img
elif transfer_style == "Shinkai":
args = parse_args()
args.weight = 'GeneratorV2_train_photo_Shinkai_init.pt'
predictor = Predictor(args.weight, args.device)
anime_img = predictor.transform_image(image)
return anime_img
elif transfer_style == "Kon Satoshi":
args = parse_args()
args.weight = 'GeneratorV2_train_photo_Paprika_init.pt'
predictor = Predictor(args.weight, args.device)
anime_img = predictor.transform_image(image)
return anime_img
else:
return image
def transfer_video(video, transfer_style):
if transfer_style == "Hayao":
#output = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)# 转换为灰度图像
#os.system("wget https://huggingface.co/YANGYYYY/cartoonize/resolve/main/GeneratorV2_train_photo_Hayao_init.pt")
args = parse_args_video()
anime_video = Predictor(args.weight).transform_video(video, args.batch_size, start=args.start, end=args.end)
return anime_video
elif transfer_style == "Shinkai":
args = parse_args()
args.weight = 'GeneratorV2_train_photo_Shinkai_init.pt'
predictor = Predictor(args.weight, args.device)
anime_img = predictor.transform_image(image)
return anime_img
elif transfer_style == "Kon Satoshi":
args = parse_args()
args.weight = 'GeneratorV2_train_photo_Paprika_init.pt'
predictor = Predictor(args.weight, args.device)
anime_img = predictor.transform_image(image)
return anime_img
else:
return image
def clear_output(input_widget):
input_widget = np.array([])
with gr.Blocks() as demo:
gr.Markdown("Transfer image or video files using this demo.")
with gr.Tabs():
with gr.TabItem("Transfer Image"):
with gr.Row():
image_input = gr.Image()
image_output = gr.Image()
with gr.Row():
image_dropdown = gr.Dropdown(label="Transfer Style",choices=["Hayao", "Shinkai", "Kon Satoshi"])
image_button = gr.Button("Transfer")
clear_image_button = gr.Button("Clear")
with gr.TabItem("Transfer Video"):
with gr.Row():
video_input = gr.Video()
video_output = gr.Video()
with gr.Row():
video_dropdown = gr.Dropdown(label="Transfer Style",choices=["Hayao", "Shinkai", "Kon Satoshi"])
video_button = gr.Button("Transfer")
clear_video_button = gr.Button("Clear")
image_button.click(transfer, inputs=[image_input,image_dropdown], outputs=image_output)
video_button.click(transfer_video, inputs=[video_input,video_dropdown], outputs=video_output)
clear_image_button.click(clear_output, inputs=image_input,outputs=image_output)
clear_video_button.click(clear_output, inputs=video_input,outputs=video_output)
demo.launch()
# 启动接口
#demo.launch(server_name='127.0.0.1',server_port=7788)
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