python/main.py

import argparse
import os
from whisper import Whisper
import time


def get_args():
    parser = argparse.ArgumentParser(
        prog="whisper",
        description="Run Whisper on input audio file"
    )
    parser.add_argument("--wav", "-w", type=str, required=True, help="Input audio file")
    parser.add_argument("--model_type", "-t", type=str, choices=["tiny", "base", "small", "large", "large-v3", "turbo"], required=True, help="model type, only support tiny, base and small currently")
    parser.add_argument("--model_path", "-p", type=str, required=False, default="../models/models-ax650", help="model path for *.axmodel, tokens.txt, positional_embedding.bin")
    parser.add_argument("--language", "-l", type=str, required=False, default="zh", help="Target language, support en, zh, ja, and others. See languages.py for more options.")
    parser.add_argument("--task", type=str, required=False, choices=["translate", "transcribe"], default="transcribe")
    parser.add_argument("--print_rtf", action="store_true", help="Print Real-Time Factor")
    return parser.parse_args()


def print_args(args):
    print(f"wav: {args.wav}")
    print(f"model_type: {args.model_type}")
    print(f"model_path: {args.model_path}")
    print(f"language: {args.language}")
    print(f"task: {args.task}")


def main():
    args = get_args()
    print_args(args)

    # Check wav existence
    wav_path = args.wav
    assert os.path.exists(wav_path), f"{wav_path} NOT exist"

    model = Whisper(args.model_type, args.model_path, args.language, args.task)

    
    
    print("\n预测结果:")
    start = time.time()
    print(model.run(wav_path))
    end = time.time()

    if args.print_rtf:
        import librosa
        samples, sr = librosa.load(wav_path, sr=16000)
        duration = len(samples) / sr
        process_time = end - start
        print(f"RTF: {process_time / duration}")

if __name__ == "__main__":
    main()