1.下载源码地址

https://github.com/Mukosame/Anime2Sketch

2. 下载项目依赖包，下载模型权重文件
   
   运行看效果

python test.py --dataroot=E:\01_hjz\datas\00-hjz\pictures --load_size=512

调整自定义测试图片路径

"""Test script for anime-to-sketch translation
Example:
    python3 test.py --dataroot /your_path/dir --load_size 512
    python3 test.py --dataroot /your_path/img.jpg --load_size 512

    python3 test.py --dataroot D:\ai\test\sumiao --load_size 512 --output_dir D:\ai\test\sumiao
"""

import os
import torch
from anime2Sketch.model_anime2sketch import create_anime2sketch_model
from anime2Sketch.data import read_img_path, tensor_to_img, save_image
import argparse

parser = argparse.ArgumentParser(description='Anime-to-sketch test options.')
parser.add_argument('--dataroot', '-i', default='test_samples/', type=str)
parser.add_argument('--load_size', '-s', default=512, type=int)
parser.add_argument('--output_dir', '-o', default='results/', type=str)
parser.add_argument('--gpu_ids', '-g', default=[], help="gpu ids: e.g. 0 0,1,2 0,2.")
opt = parser.parse_args()

# create model
gpu_list = ','.join(str(x) for x in opt.gpu_ids)
os.environ['CUDA_VISIBLE_DEVICES'] = gpu_list
device = torch.device('cuda' if len(opt.gpu_ids) > 0 else 'cpu')
print(device)
model = create_anime2sketch_model().to(device)  # create a model given opt.model and other options
model.eval()

def chose_image(source_image_path, output_folder_path):
    # img = cv2.imread(source_image_path)

    save_dir = output_folder_path
    #os.makedirs(save_dir, exist_ok=True)
    # test_path ='D:\\ai\\test\sumiao\\5.jpg';
    print(source_image_path)
    basename = os.path.basename(source_image_path)
    #print(basename)
    aus_path = os.path.join(save_dir,basename.split(".")[0] +"_cutout.png")
    #print(aus_path)
    img, aus_resize = read_img_path(source_image_path, opt.load_size)
    aus_tensor = model(img.to(device))
    aus_img = tensor_to_img(aus_tensor)
    save_image(aus_img, aus_path, aus_resize)


if __name__ == '__main__':


    file_path = r"D:\work-mengyi\photo\miniprogram\static\images\default.jpg"

    base_name = os.path.basename(file_path)
    print(base_name)
    # 20200708002140.jpg

    suffix = base_name.split(".")[1]
    print("suffix: {}".format(suffix))
    # suffix: jpg

    suffix = base_name.split(".")[0]
    print("filename2222: {}".format(suffix))
    # filename: 20200708002140

    base_name = os.path.dirname(file_path)
    print(base_name)

    # d:\aaaa
    #chose_image('D:\\ai\\test\\sumiao\\5.jpg', 'D:\\ai\\test\\sumiao')
    # get input data
    # if os.path.isdir(opt.dataroot):
    #     test_list = get_image_list(opt.dataroot)
    # elif os.path.isfile(opt.dataroot):
    #     test_list = [opt.dataroot]
    # else:
    #     raise Exception("{} is not a valid directory or image file.".format(opt.dataroot))
    # save outputs

    # for test_path in tqdm(test_list):
    #     print(test_path)
    #     basename = os.path.basename(test_path)
    #     print(basename)
    #     aus_path = os.path.join(save_dir, basename)
    #     print(aus_path)
    #     img,  aus_resize = read_img_path(test_path, opt.load_size)
    #     aus_tensor = model(img.to(device))
    #     aus_img = tensor_to_img(aus_tensor)
    #     save_image(aus_img, aus_path, aus_resize)

体验地址：