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import argparse | |
from moviepy.editor import VideoFileClip | |
import whisper | |
import os | |
import re | |
def extract_audio(video_path, audio_dir='./audio'): | |
os.makedirs(audio_dir, exist_ok=True) | |
base_filename = os.path.splitext(os.path.basename(video_path))[0] | |
audio_filename = os.path.join(audio_dir, base_filename + '.wav') | |
video_clip = VideoFileClip(video_path) | |
video_clip.audio.write_audiofile(audio_filename) | |
video_clip.close() | |
return audio_filename | |
def transcribe_audio(audio_path, model_type='base', transcribed_dir='./transcribed'): | |
model = whisper.load_model(model_type) | |
result = model.transcribe(audio_path) | |
os.makedirs(transcribed_dir, exist_ok=True) | |
base_filename = os.path.splitext(os.path.basename(audio_path))[0] | |
transcribed_filename = os.path.join(transcribed_dir, base_filename + '.txt') | |
with open(transcribed_filename, 'w') as file: | |
for segment in result['segments']: | |
start = segment['start'] | |
end = segment['end'] | |
text = segment['text'] | |
file.write(f"[{start:.2f}-{end:.2f}] {text}\n") | |
return transcribed_filename, result['text'] | |
def merge_lines(file_path): | |
timestamp_pattern = re.compile(r'\[(\d+\.\d+)-(\d+\.\d+)\]') | |
with open(file_path, 'r') as file: | |
lines = file.readlines() | |
merged_lines = [] | |
i = 0 | |
while i < len(lines): | |
line = lines[i].strip() | |
match = timestamp_pattern.match(line) | |
if match: | |
start_time = float(match.group(1)) | |
text = line[match.end():].strip() | |
if not (text.endswith('.') or text.endswith('?')): | |
if i + 1 < len(lines): | |
next_line = lines[i + 1].strip() | |
next_match = timestamp_pattern.match(next_line) | |
if next_match: | |
end_time = float(next_match.group(2)) | |
next_text = next_line[next_match.end():].strip() | |
merged_text = text + ' ' + next_text | |
merged_line = f"[{start_time:.2f}-{end_time:.2f}] {merged_text}\n" | |
merged_lines.append(merged_line) | |
i += 1 | |
else: | |
end_time = float(match.group(2)) | |
merged_lines.append(f"[{start_time:.2f}-{end_time:.2f}] {text}\n") | |
i += 1 | |
with open(file_path, 'w') as file: | |
file.writelines(merged_lines) | |
return file_path | |
def convert_video_to_text(video_file_path, model_type='base'): | |
audio_path = extract_audio(video_file_path) | |
transcribed_path, _ = transcribe_audio(audio_path, model_type) | |
merge_lines(transcribed_path) | |
return transcribed_path | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser(description="Transcribe audio from video") | |
parser.add_argument("video_file", help="Path to the video file") | |
parser.add_argument("--model", help="Size of the whisper model (e.g., tiny, base, small, medium, large, huge).", default="base") | |
args = parser.parse_args() | |
convert_video_to_text(args.video_file, args.model) | |