# base64是一种将不可见字符转换为可见字符的编码方式
import base64
# opencv是跨平台计算机视觉库，实现了图像处理和计算机视觉方面的很多通用算法
import osimport cv2
import requests
from aip import AipOcr
# 百度AI的文字识别库

def tailor_video():# 要提取视频的文件名，隐藏后缀sourceFileName = 'material'# 在这里把后缀接上video_path = os.path.join("G:/material/", sourceFileName + '.mp4')times = 0# 提取视频的频率，每10帧提取一个frameFrequency = 10# 输出图片到当前目录video文件夹下outPutDirName = 'G:/material/video/' + sourceFileName + '/'if not os.path.exists(outPutDirName):# 如果文件目录不存在则创建目录os.makedirs(outPutDirName)camera = cv2.VideoCapture(video_path)while True:times += 1res, image = camera.read()if not res:print('not res , not image')breakif times % frameFrequency == 0:cv2.imwrite(outPutDirName + str(times) + '.jpg', image)  #文件目录下将输出的图片名字命名为10.jpg这种形式print(outPutDirName + str(times) + '.jpg')print('图片提取结束')

def text_create(name, msg):desktop_path = "G:/material/"  # 新创建的txt文件的存放路径full_path = desktop_path + name + '.txt'  # 也可以创建一个.doc的word文档file = open(full_path, 'w')file.write(msg)file.close()

# 定义一个函数，用来判断是否是中文，是中文的话就返回True代表要提取中文字幕
def is_Chinese(word):for ch in word:if 'u4e00' <= ch <= 'u9fff':return Truereturn False

def tailor(path1,path2,begin,end,step_size):  #截取字幕for i in range(begin,end,step_size):fname1=path1 % str(i)print(fname1)img = cv2.imread(fname1)print(img.shape)cropped = img[500:600, 100:750]  # 裁剪坐标为[y0:y1, x0:x1]imgray = cv2.cvtColor(cropped, cv2.COLOR_BGR2GRAY)thresh = 200ret, binary = cv2.threshold(imgray, thresh, 255, cv2.THRESH_BINARY)  # 输入灰度图，输出二值图binary1 = cv2.bitwise_not(binary)  # 取反cv2.imwrite(path2 % str(i), binary1)

# 定义一个函数，用来访问百度API，
def requestApi(img):request_url = "https://aip.baidubce.com/rest/2.0/ocr/v1/general_basic"params = {"image": img,'language_type':'CHN_ENG'}access_token = '24.b802cd212b0e702b018f999c594b6d9f.2592000.1589466832.282335-19430506'request_url = request_url + "?access_token=" + access_tokenheaders = {'content-type': 'application/x-www-form-urlencoded'}response = requests.post(request_url, data=params, headers=headers)results=response.json()return results

def get_file_content(filePath):with open(filePath, 'rb') as fp:# 将读取出来的图片转换为b64encode编码格式return base64.b64encode(fp.read())
# 定义函数字幕，用来对字幕进行操作
# step_size 步长
def subtitle(fname,begin,end,step_size):array =[] #定义一个数组用来存放wordsfor i in range(begin,end,step_size):  #begin开始，end结束，循环按照步长step_size遍历，共有419张图片，也就是（1,420,10）fname1=fname % str(i)print(fname1)image = get_file_content(fname1)try:results=requestApi(image)['words_result']  #调用requestApi函数，获取json字符串中的words_resultfor item in results:print(results)if is_Chinese(item['words']):array.append(item['words'].replace('猎奇笔记本', '')) # 将图片中不需要的字幕“猎奇笔记本”替换为空except Exception as e:print(e)text=''result = list(set(array))  # 将array数组准换为一个无序不重复元素集达到去重的效果，再转为列表result.sort(key=array.index) # 利用sort将数组中的元素即字幕重新排序，达到视频播放字幕的顺序for item in result:print(item)text+=item+'n'text_create('test1',text)

if __name__ =="__main__":path1 = 'G:/material/video/img/%s.jpg'  # 视频转为图片存放的路径（帧）path2 = 'G:/material/video/img2/%s.jpg'  # 图片截取字幕后存放的路径print("""1.图片裁剪2.提取字幕3.裁剪视频""")choose=input()begin=100end=1000step_size=10if choose=='1':tailor(path1,path2,begin,end,step_size)if choose=='2':subtitle(path2,begin,end,step_size)if choose=='3':tailor_video()