27 lines
693 B
Python
27 lines
693 B
Python
from emo_gen import EmotionModel, process_func
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import librosa
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import numpy as np
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import torch
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from transformers import Wav2Vec2Processor
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from config import config
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model_name = "./emotional/wav2vec2-large-robust-12-ft-emotion-msp-dim"
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device = "cuda" if torch.cuda.is_available() else "cpu"
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processor = Wav2Vec2Processor.from_pretrained(model_name)
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model = EmotionModel.from_pretrained(model_name).to(device)
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def get_emo(path):
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wav, sr = librosa.load(path, 16000)
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device = config.bert_gen_config.device
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return process_func(
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np.expand_dims(wav, 0).astype(np.float),
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sr,
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model,
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processor,
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device,
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embeddings=True,
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).squeeze(0)
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