From e9d2cfc3a134b00f4e98271fbee3838d1ccecbcc Mon Sep 17 00:00:00 2001
From: VirtuosoQ <2416050435@qq.com>
Date: 星期五, 26 四月 2024 14:59:30 +0800
Subject: [PATCH] FunASR java http  client

---
 funasr/frontends/whisper_frontend.py |   22 ++++++++++++++++------
 1 files changed, 16 insertions(+), 6 deletions(-)

diff --git a/funasr/frontends/whisper_frontend.py b/funasr/frontends/whisper_frontend.py
index 0598c61..acc99af 100644
--- a/funasr/frontends/whisper_frontend.py
+++ b/funasr/frontends/whisper_frontend.py
@@ -1,8 +1,8 @@
 from typing import Tuple
 import torch
 import torch.nn as nn
-import whisper
-from whisper.audio import HOP_LENGTH, N_FFT, N_SAMPLES
+
+
 from funasr.register import tables
 from torch.nn.utils.rnn import pad_sequence
 
@@ -26,7 +26,8 @@
         super().__init__()
         assert fs == 16000
         self.fs = fs
-
+        import whisper
+        from whisper.audio import HOP_LENGTH, N_FFT, N_SAMPLES
         self.n_fft = N_FFT
         self.win_length = N_FFT
         self.hop_length = HOP_LENGTH
@@ -37,7 +38,13 @@
         if whisper_model == "large-v3" or whisper_model == "large":
             self.n_mels = 128
 
-        self.mel_filters = whisper.audio.mel_filters
+        filters_path = kwargs.get("filters_path", None)
+        self.filters_path = filters_path
+        if filters_path is not None:
+            from funasr.models.sense_voice.whisper_lib.audio import mel_filters
+            self.mel_filters = mel_filters
+        else:
+            self.mel_filters = whisper.audio.mel_filters
         self.do_pad_trim = do_pad_trim
         if do_pad_trim:
             self.pad_or_trim = whisper.pad_or_trim
@@ -60,8 +67,10 @@
 
         # whisper deletes the last frame by default (Shih-Lun)
         magnitudes = stft[..., :-1].abs() ** 2
-
-        filters = self.mel_filters(audio.device, self.n_mels)
+        if self.filters_path is not None:
+            filters = self.mel_filters(audio.device, self.n_mels, self.filters_path)
+        else:
+            filters = self.mel_filters(audio.device, self.n_mels)
         mel_spec = filters @ magnitudes
 
         log_spec = torch.clamp(mel_spec, min=1e-10).log10()
@@ -85,6 +94,7 @@
         batch_size = input.size(0)
         feats = []
         feats_lens = []
+        input = input.to(torch.float32)
         for i in range(batch_size):
             if self.do_pad_trim:
                 feat = self.pad_or_trim(input[i], self.pad_samples)

--
Gitblit v1.9.1