126 lines
3.9 KiB
Python
126 lines
3.9 KiB
Python
from __future__ import annotations
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from concurrent import futures
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import datetime
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import pytesseract
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import cv2
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import timeit
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from .models import PredictedFrame, PredictedSubtitle
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class Video:
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path: str
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lang: str
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use_fullframe: bool
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num_frames: int
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fps: float
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pred_frames: List[PredictedFrame]
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pred_subs: List[PredictedSubtitle]
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def __init__(self, path, lang, use_fullframe=False):
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self.path = path
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self.lang = lang
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self.use_fullframe = use_fullframe
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v = cv2.VideoCapture(path)
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self.num_frames = int(v.get(cv2.CAP_PROP_FRAME_COUNT))
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self.fps = v.get(cv2.CAP_PROP_FPS)
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v.release()
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def _single_frame_ocr(self, img) -> str:
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if not self.use_fullframe:
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# only use bottom half of the frame by default
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img = img[img.shape[0] // 2:, :]
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data = pytesseract.image_to_data(img, lang=self.lang)
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return data
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def run_ocr(self) -> None:
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v = cv2.VideoCapture(self.path)
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frames = (v.read()[1] for _ in range(self.num_frames))
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# perform ocr to all frames in parallel
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with futures.ProcessPoolExecutor() as pool:
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frames_ocr = pool.map(self._single_frame_ocr, frames, chunksize=10)
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self.pred_frames = [PredictedFrame(i, data)
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for i, data in enumerate(frames_ocr)]
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v.release()
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def get_subtitles(self) -> str:
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self._generate_subtitles()
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return ''.join(
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'{}\n{} --> {}\n{}\n\n'.format(
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i,
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self._srt_timestamp(sub.index_start),
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self._srt_timestamp(sub.index_end),
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sub.text)
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for i, sub in enumerate(self.pred_subs))
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def _generate_subtitles(self) -> None:
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self.pred_subs = []
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if self.pred_frames is None:
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raise AttributeError(
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'Please call self.run_ocr() first to perform ocr on frames')
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# divide ocr of frames into subtitle paragraphs using sliding window
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WIN_BOUND = int(self.fps // 2) # 1/2 sec sliding window boundary
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bound = WIN_BOUND
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i = 0
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j = 1
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while j < self.num_frames:
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fi, fj = self.pred_frames[i], self.pred_frames[j]
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if fi.is_similar_to(fj):
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bound = WIN_BOUND
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elif bound > 0:
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bound -= 1
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else:
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# divide subtitle paragraphs
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para_new = j - WIN_BOUND
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self._append_sub(
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PredictedSubtitle(self.pred_frames[i:para_new]))
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i = para_new
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j = i
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bound = WIN_BOUND
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j += 1
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# also handle the last remaining frames
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if i < self.num_frames - 1:
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self._append_sub(PredictedSubtitle(self.pred_frames[i:]))
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def _append_sub(self, sub: PredictedSubtitle) -> None:
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if len(sub.text) == 0:
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return
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# merge new sub to the last subs if they are similar
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while self.pred_subs and sub.is_similar_to(self.pred_subs[-1]):
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ls = self.pred_subs[-1]
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del self.pred_subs[-1]
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sub = PredictedSubtitle(ls.frames + sub.frames)
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self.pred_subs.append(sub)
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def _srt_timestamp(self, frame_index: int) -> str:
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td = datetime.timedelta(seconds=frame_index / self.fps)
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ms = td.microseconds // 1000
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m, s = divmod(td.seconds, 60)
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h, m = divmod(m, 60)
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return '{:02d}:{:02d}:{:02d},{:03d}'.format(h, m, s, ms)
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def save_subtitles_to_file(self, path='subtitle.srt') -> None:
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with open(path, 'w+') as f:
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f.write(self.get_subtitles())
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time_start = timeit.default_timer()
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v = Video('1.mp4', 'HanS')
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v.run_ocr()
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time_stop = timeit.default_timer()
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print('time for ocr: ', time_stop - time_start)
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time_start = timeit.default_timer()
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v.save_subtitles_to_file()
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time_stop = timeit.default_timer()
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print('time for save sub: ', time_stop - time_start)
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