mirror of https://github.com/JavMB/ejercicios
42 lines
1.2 KiB
Python
42 lines
1.2 KiB
Python
import torch
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import whisper
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def cuda_works():
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print(torch.cuda.is_available())
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print(torch.cuda.get_device_name(0))
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def format_time(seconds):
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ms = int((seconds - int(seconds)) * 1000)
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s = int(seconds) % 60
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m = (int(seconds) // 60) % 60
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h = int(seconds) // 3600
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return f"{h:02}:{m:02}:{s:02},{ms:03}"
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def generate_subtitles(video_path):
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model_name = "medium"
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model = whisper.load_model(model_name)
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result = model.transcribe(video_path, task="translate", language="es")
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srt_path = "subtitles.srt"
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with open(srt_path, "w", encoding="utf-8") as srt_file:
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for segment in result["segments"]:
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start = segment["start"]
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end = segment["end"]
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text = segment["text"]
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srt_file.write(f"{segment['id'] + 1}\n")
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srt_file.write(f"{format_time(start)} --> {format_time(end)}\n")
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srt_file.write(f"{text}\n\n")
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print(f"Subtítle generated in path: {srt_path}")
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if __name__ == "__main__":
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# cuda_works()
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generate_subtitles(
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r"C:\Users\david\Videos\Social media\Cursos\Spring Security\Introduccion\Introducción Curso Spring Security Cero a Experto.mp4")
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