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FakeVideoDetect
File size: 4,331 Bytes 
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from multiprocessing import Pool
from PIL import Image
import sys

# sys.path.append('/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/code_test')

# from imageocr import imageocr
# from Extract_audio import extract_audio
from FakeVD.code_test.VGGish_Feature_Extractor.my_vggish_fun import vggish_audio as extract_audio
from FakeVD.code_test.VGG19_Feature_Extractor.vgg19_feature import load_model_vgg19

# from Imghash import imghash
# from Extract_frame import V2frame
from FakeVD.code_test.Text_Feature_Extractor.wav2text import wav2text
import os
import shutil
# from Sentence_distance import sentence_distance
import time
import json
import cv2
# audio_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/dataset/1.wav'
# frame_path = ''
# datasave_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/code_test/Text_Feature/data'
# video_path = '/mnt/data10t/dazuoye/GROUP2024-GEN6/FakeSV/code_test/Text_Feature/videos'

# def get_string_from_list(A):
#     if type(A) == list:
#         ret = ''
#         for i in A:
#             ret += get_string_from_list(i)
#         return ret
#     if type(A) == str:
#         return A
#     return ""


# ocr_ret = []


# def ocr_frame(frame):
#     img_path = os.path.join(frame_path, str(frame)+'.jpg')
#     now_ocr_result = imageocr.work(img_path)
#     ocr_ret.append({'frame': frame, 'result': now_ocr_result})


# def get_frame(x):
#     return x['frame']


# def OCR(path):
#     imgH = imghash()
#     cropimgH = imghash()
#     # 返回结果
#     ret = []

#     # 当前帧
#     now_frame = -15
#     # 上一次执行ocr的帧
#     last_frame = 0
#     # 上一次的ocr结果拼接字符串
#     last_ocr_result_string = "ocr at first"
#     # 限
#     k = 8
#     # 历史最高k点
#     kmax = 20
#     # 匹配标识
#     marchflag = False

#     while True:
#         now_frame += 15

#         img_path = os.path.join(frame_path, str(now_frame)+'.jpg')

#         if not os.path.exists(img_path):
#             print('[OCR all] done', now_frame)
#             break

#         # 相似度高，无需ocr
#         if not imgH.work(Image.open(img_path), k):
#             print("continue " + str(now_frame))
#             continue

#         print('[OCR working] ocr at frame', now_frame)

#         # 进行ocr
#         now_ocr_result = imageocr.work(img_path, cropimgH)

#         # 将识别结果添加
#         ret.append({'frame': now_frame, 'result': now_ocr_result})
#         # print('[OCR done] ocr at frame', now_frame)
#     return ret


# 处理视频
def video_work(w2t, model_vggish, video_file_path, output_path, audio_path='./FakeVD/code_test/preprocessed_feature/1.wav'):
    video_file_name = os.path.basename(video_file_path)
    video_id = os.path.splitext(video_file_name)[0]
    
    st = time.time()
    print('[video_work] working')
    # v2f = V2frame()

    ##################
    # w2t = wav2text()

    # 分离wav
    print('[extract audio]', video_file_path, audio_path)
    extract_audio(model_vggish, video_file_path, feature_path="./FakeVD/code_test/preprocessed_feature/1.pkl", audio_file_path=audio_path)
    # 分离帧
    # print('[extract frame]', path, audio_path)
    # v2f.work(path, frame_path)

    # 进行wav处理
    print('[wav2text] working')
    wav_result = w2t.work(audio_path)
    #print('[wav_result]', wav_result)

    # 进行ocr处理
    # ocr_result = OCR(frame_path)
    # print('ocr_result', ocr_result)

    # cap = cv2.VideoCapture(path)
    # fps = cap.get(cv2.CAP_PROP_FPS)

    print("time:     " + str(time.time() - st))

    result = {"video_id": video_id, 'text': wav_result[0]['text']} # , 'ocr_result': ocr_result , "fps": fps

    with open(output_path, 'w') as f:
        f.write(json.dumps(result, ensure_ascii=False))


# if __name__ == '__main__':
    # file = sys.argv[1]
    # r = open(file, "r").readlines()
    # for name in r:
    #     name = name.strip()
    #     data_path = os.path.join(datasave_path, name[:-4]+'.json')
    #     if os.path.exists(data_path):
    #         # print("continue " + name)
    #         continue
    #     if name == '':
    #         continue
    #     path = os.path.join(video_path, name)

    #     result = video_work(path, name[:-4])

    #     with open(data_path, 'w') as f:
    #         f.write(json.dumps(result, ensure_ascii=False))