From a1447d12cc7b18a260a4d1cd8ff572f8e78eaba4 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期五, 03 三月 2023 11:14:23 +0800
Subject: [PATCH] set ploter default to False
---
funasr/runtime/python/onnxruntime/rapid_paraformer/paraformer_onnx.py | 32 +++++++++++++++++++++++++++++---
1 files changed, 29 insertions(+), 3 deletions(-)
diff --git a/funasr/runtime/python/onnxruntime/rapid_paraformer/paraformer_onnx.py b/funasr/runtime/python/onnxruntime/rapid_paraformer/paraformer_onnx.py
index ed9b030..4a55bdf 100644
--- a/funasr/runtime/python/onnxruntime/rapid_paraformer/paraformer_onnx.py
+++ b/funasr/runtime/python/onnxruntime/rapid_paraformer/paraformer_onnx.py
@@ -1,6 +1,7 @@
# -*- encoding: utf-8 -*-
# @Author: SWHL
# @Contact: liekkaskono@163.com
+from cgitb import text
import os.path
from pathlib import Path
from typing import List, Union, Tuple
@@ -23,6 +24,7 @@
def __init__(self, model_dir: Union[str, Path] = None,
batch_size: int = 1,
device_id: Union[str, int] = "-1",
+ plot_timestamp: bool = False,
):
if not Path(model_dir).exists():
@@ -41,17 +43,16 @@
)
self.ort_infer = OrtInferSession(model_file, device_id)
self.batch_size = batch_size
+ self.plot = plot_timestamp
def __call__(self, wav_content: Union[str, np.ndarray, List[str]], **kwargs) -> List:
waveform_list = self.load_data(wav_content, self.frontend.opts.frame_opts.samp_freq)
waveform_nums = len(waveform_list)
-
asr_res = []
for beg_idx in range(0, waveform_nums, self.batch_size):
res = {}
end_idx = min(waveform_nums, beg_idx + self.batch_size)
feats, feats_len = self.extract_feat(waveform_list[beg_idx:end_idx])
-
try:
outputs = self.infer(feats, feats_len)
am_scores, valid_token_lens = outputs[0], outputs[1]
@@ -68,11 +69,36 @@
preds, raw_token = self.decode(am_scores, valid_token_lens)[0]
res['preds'] = preds
if us_cif_peak is not None:
- timestamp = time_stamp_lfr6_onnx(us_cif_peak, copy.copy(raw_token))
+ timestamp, timestamp_total = time_stamp_lfr6_onnx(us_cif_peak, copy.copy(raw_token))
res['timestamp'] = timestamp
+ if self.plot:
+ self.plot_wave_timestamp(waveform_list[0], timestamp_total)
asr_res.append(res)
return asr_res
+ def plot_wave_timestamp(self, wav, text_timestamp):
+ # TODO: Plot the wav and timestamp results with matplotlib
+ import matplotlib
+ matplotlib.use('Agg')
+ matplotlib.rc("font", family='Alibaba PuHuiTi') # set it to a font that your system supports
+ import matplotlib.pyplot as plt
+ fig, ax1 = plt.subplots(figsize=(11, 3.5), dpi=320)
+ ax2 = ax1.twinx()
+ ax2.set_ylim([0, 2.0])
+ # plot waveform
+ ax1.set_ylim([-0.3, 0.3])
+ time = np.arange(wav.shape[0]) / 16000
+ ax1.plot(time, wav/wav.max()*0.3, color='gray', alpha=0.4)
+ # plot lines and text
+ for (char, start, end) in text_timestamp:
+ ax1.vlines(start, -0.3, 0.3, ls='--')
+ ax1.vlines(end, -0.3, 0.3, ls='--')
+ x_adj = 0.045 if char != '<sil>' else 0.12
+ ax1.text((start + end) * 0.5 - x_adj, 0, char)
+ # plt.legend()
+ plotname = "funasr/runtime/python/onnxruntime/debug.png"
+ plt.savefig(plotname, bbox_inches='tight')
+
def load_data(self,
wav_content: Union[str, np.ndarray, List[str]], fs: int = None) -> List:
def load_wav(path: str) -> np.ndarray:
--
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