conda create -n dctnet python=3.8
conda activate dctnet
pip install torch-1.10.0+cu113-cp38-cp38-win_amd64.whl
pip install torchvision-0.11.0+cu113-cp38-cp38-win_amd64.whl
pip install opencv-python -i https://mirror.baidu.com/pypi/simple
pip install tensorflow==2.8.0 -i https://mirror.baidu.com/pypi/simple
pip install protobuf==3.20.1 -i https://mirror.baidu.com/pypi/simple
pip install easydict -i https://mirror.baidu.com/pypi/simple
pip install numpy==1.22 -i https://mirror.baidu.com/pypi/simple

import cv2
from source.cartoonize import Cartoonizer
import os
import numpy as np
from socket import *


def get_model_list(model_dir):
    list_models = []
    m_dirs = os.listdir(model_dir)
    for dir in m_dirs:
        path_model = os.path.join(model_dir,dir)
        list_models.append(path_model)
    return list_models


def katong_video(i):
    list_models = get_model_list("models")
    print(list_models)
    algo =Cartoonizer(list_models[i])

    cap = cv2.VideoCapture(0)
    cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1080)
    cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 640)


    while True:
        success,img = cap.read()
        if  success:
            # 增加亮度
            # alpha = 1.1  # 增加的倍数
            # beta = 30  # 增加的常量值
            # img = cv2.addWeighted(img, alpha, np.zeros(img.shape, dtype=img.dtype), 0, beta)
            brightness = 30  # 亮度增益，可以改变数值试试效果
            img = cv2.addWeighted(img, 1 + brightness / 100, img, 0, 0)
            result = algo.cartoonize(img[...,::-1]
            cv2.imshow('video',np.array(result,dtype=np.uint8))
        else:
            break
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break
    cap.release()

if __name__ == '__main__':
# i是模型的不同风格
    i = 5
    katong_video(i)