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https://github.com/babysor/MockingBird.git
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c91bc3208e
* 添加 -d 指定数据集时错误提示 Warning: you do not have any of the recognized datasets in G:\AI\Dataset\aidatatang_200zh\aidatatang_200zh Please note use 'E:\datasets' as root path instead of 'E:\datasetsidatatang_200zh\corpus/test' as a example . The recognized datasets are: * Update ui.py * Update ui.py
702 lines
28 KiB
Python
702 lines
28 KiB
Python
from PyQt5.QtCore import Qt, QStringListModel
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from PyQt5 import QtGui
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from PyQt5.QtWidgets import *
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import matplotlib.pyplot as plt
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from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
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from matplotlib.figure import Figure
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from encoder.inference import plot_embedding_as_heatmap
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from toolbox.utterance import Utterance
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from pathlib import Path
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from typing import List, Set
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import sounddevice as sd
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import soundfile as sf
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import numpy as np
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# from sklearn.manifold import TSNE # You can try with TSNE if you like, I prefer UMAP
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from time import sleep
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import umap
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import sys
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from warnings import filterwarnings, warn
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filterwarnings("ignore")
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colormap = np.array([
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[0, 127, 70],
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[255, 0, 0],
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[255, 217, 38],
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[0, 135, 255],
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[165, 0, 165],
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[255, 167, 255],
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[97, 142, 151],
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[0, 255, 255],
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[255, 96, 38],
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[142, 76, 0],
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[33, 0, 127],
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[0, 0, 0],
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[183, 183, 183],
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[76, 255, 0],
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], dtype=np.float) / 255
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default_text = \
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"欢迎使用工具箱, 现已支持中文输入！"
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class UI(QDialog):
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min_umap_points = 4
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max_log_lines = 5
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max_saved_utterances = 20
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def draw_utterance(self, utterance: Utterance, which):
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self.draw_spec(utterance.spec, which)
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self.draw_embed(utterance.embed, utterance.name, which)
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def draw_embed(self, embed, name, which):
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embed_ax, _ = self.current_ax if which == "current" else self.gen_ax
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embed_ax.figure.suptitle("" if embed is None else name)
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## Embedding
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# Clear the plot
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if len(embed_ax.images) > 0:
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embed_ax.images[0].colorbar.remove()
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embed_ax.clear()
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# Draw the embed
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if embed is not None:
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plot_embedding_as_heatmap(embed, embed_ax)
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embed_ax.set_title("embedding")
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embed_ax.set_aspect("equal", "datalim")
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embed_ax.set_xticks([])
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embed_ax.set_yticks([])
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embed_ax.figure.canvas.draw()
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def draw_spec(self, spec, which):
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_, spec_ax = self.current_ax if which == "current" else self.gen_ax
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## Spectrogram
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# Draw the spectrogram
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spec_ax.clear()
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if spec is not None:
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im = spec_ax.imshow(spec, aspect="auto", interpolation="none")
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# spec_ax.figure.colorbar(mappable=im, shrink=0.65, orientation="horizontal",
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# spec_ax=spec_ax)
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spec_ax.set_title("mel spectrogram")
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spec_ax.set_xticks([])
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spec_ax.set_yticks([])
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spec_ax.figure.canvas.draw()
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if which != "current":
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self.vocode_button.setDisabled(spec is None)
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def draw_umap_projections(self, utterances: Set[Utterance]):
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self.umap_ax.clear()
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speakers = np.unique([u.speaker_name for u in utterances])
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colors = {speaker_name: colormap[i] for i, speaker_name in enumerate(speakers)}
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embeds = [u.embed for u in utterances]
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# Display a message if there aren't enough points
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if len(utterances) < self.min_umap_points:
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self.umap_ax.text(.5, .5, "Add %d more points to\ngenerate the projections" %
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(self.min_umap_points - len(utterances)),
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horizontalalignment='center', fontsize=15)
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self.umap_ax.set_title("")
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# Compute the projections
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else:
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if not self.umap_hot:
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self.log(
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"Drawing UMAP projections for the first time, this will take a few seconds.")
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self.umap_hot = True
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reducer = umap.UMAP(int(np.ceil(np.sqrt(len(embeds)))), metric="cosine")
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# reducer = TSNE()
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projections = reducer.fit_transform(embeds)
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speakers_done = set()
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for projection, utterance in zip(projections, utterances):
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color = colors[utterance.speaker_name]
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mark = "x" if "_gen_" in utterance.name else "o"
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label = None if utterance.speaker_name in speakers_done else utterance.speaker_name
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speakers_done.add(utterance.speaker_name)
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self.umap_ax.scatter(projection[0], projection[1], c=[color], marker=mark,
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label=label)
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# self.umap_ax.set_title("UMAP projections")
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self.umap_ax.legend(prop={'size': 10})
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# Draw the plot
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self.umap_ax.set_aspect("equal", "datalim")
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self.umap_ax.set_xticks([])
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self.umap_ax.set_yticks([])
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self.umap_ax.figure.canvas.draw()
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def save_audio_file(self, wav, sample_rate):
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dialog = QFileDialog()
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dialog.setDefaultSuffix(".wav")
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fpath, _ = dialog.getSaveFileName(
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parent=self,
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caption="Select a path to save the audio file",
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filter="Audio Files (*.flac *.wav)"
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)
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if fpath:
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#Default format is wav
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if Path(fpath).suffix == "":
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fpath += ".wav"
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sf.write(fpath, wav, sample_rate)
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def setup_audio_devices(self, sample_rate):
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input_devices = []
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output_devices = []
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for device in sd.query_devices():
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# Check if valid input
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try:
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sd.check_input_settings(device=device["name"], samplerate=sample_rate)
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input_devices.append(device["name"])
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except:
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pass
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# Check if valid output
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try:
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sd.check_output_settings(device=device["name"], samplerate=sample_rate)
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output_devices.append(device["name"])
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except Exception as e:
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# Log a warning only if the device is not an input
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if not device["name"] in input_devices:
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warn("Unsupported output device %s for the sample rate: %d \nError: %s" % (device["name"], sample_rate, str(e)))
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if len(input_devices) == 0:
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self.log("No audio input device detected. Recording may not work.")
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self.audio_in_device = None
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else:
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self.audio_in_device = input_devices[0]
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if len(output_devices) == 0:
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self.log("No supported output audio devices were found! Audio output may not work.")
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self.audio_out_devices_cb.addItems(["None"])
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self.audio_out_devices_cb.setDisabled(True)
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else:
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self.audio_out_devices_cb.clear()
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self.audio_out_devices_cb.addItems(output_devices)
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self.audio_out_devices_cb.currentTextChanged.connect(self.set_audio_device)
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self.set_audio_device()
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def set_audio_device(self):
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output_device = self.audio_out_devices_cb.currentText()
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if output_device == "None":
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output_device = None
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# If None, sounddevice queries portaudio
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sd.default.device = (self.audio_in_device, output_device)
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def play(self, wav, sample_rate):
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try:
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sd.stop()
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sd.play(wav, sample_rate)
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except Exception as e:
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print(e)
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self.log("Error in audio playback. Try selecting a different audio output device.")
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self.log("Your device must be connected before you start the toolbox.")
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def stop(self):
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sd.stop()
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def record_one(self, sample_rate, duration):
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self.record_button.setText("Recording...")
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self.record_button.setDisabled(True)
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self.log("Recording %d seconds of audio" % duration)
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sd.stop()
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try:
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wav = sd.rec(duration * sample_rate, sample_rate, 1)
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except Exception as e:
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print(e)
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self.log("Could not record anything. Is your recording device enabled?")
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self.log("Your device must be connected before you start the toolbox.")
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return None
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for i in np.arange(0, duration, 0.1):
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self.set_loading(i, duration)
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sleep(0.1)
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self.set_loading(duration, duration)
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sd.wait()
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self.log("Done recording.")
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self.record_button.setText("Record")
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self.record_button.setDisabled(False)
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return wav.squeeze()
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@property
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def current_dataset_name(self):
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return self.dataset_box.currentText()
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@property
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def current_speaker_name(self):
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return self.speaker_box.currentText()
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@property
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def current_utterance_name(self):
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return self.utterance_box.currentText()
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def browse_file(self):
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fpath = QFileDialog().getOpenFileName(
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parent=self,
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caption="Select an audio file",
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filter="Audio Files (*.mp3 *.flac *.wav *.m4a)"
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)
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return Path(fpath[0]) if fpath[0] != "" else ""
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@staticmethod
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def repopulate_box(box, items, random=False):
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"""
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Resets a box and adds a list of items. Pass a list of (item, data) pairs instead to join
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data to the items
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"""
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box.blockSignals(True)
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box.clear()
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for item in items:
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item = list(item) if isinstance(item, tuple) else [item]
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box.addItem(str(item[0]), *item[1:])
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if len(items) > 0:
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box.setCurrentIndex(np.random.randint(len(items)) if random else 0)
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box.setDisabled(len(items) == 0)
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box.blockSignals(False)
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def populate_browser(self, datasets_root: Path, recognized_datasets: List, level: int,
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random=True):
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# Select a random dataset
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if level <= 0:
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if datasets_root is not None:
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datasets = [datasets_root.joinpath(d) for d in recognized_datasets]
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datasets = [d.relative_to(datasets_root) for d in datasets if d.exists()]
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self.browser_load_button.setDisabled(len(datasets) == 0)
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if datasets_root is None or len(datasets) == 0:
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msg = "Warning: you d" + ("id not pass a root directory for datasets as argument" \
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if datasets_root is None else "o not have any of the recognized datasets" \
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" in %s \n" \
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"Please note use 'E:\datasets' as root path " \
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"instead of 'E:\datasets\aidatatang_200zh\corpus\test' as an example " % datasets_root)
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self.log(msg)
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msg += ".\nThe recognized datasets are:\n\t%s\nFeel free to add your own. You " \
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"can still use the toolbox by recording samples yourself." % \
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("\n\t".join(recognized_datasets))
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print(msg, file=sys.stderr)
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self.random_utterance_button.setDisabled(True)
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self.random_speaker_button.setDisabled(True)
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self.random_dataset_button.setDisabled(True)
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self.utterance_box.setDisabled(True)
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self.speaker_box.setDisabled(True)
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self.dataset_box.setDisabled(True)
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self.browser_load_button.setDisabled(True)
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self.auto_next_checkbox.setDisabled(True)
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return
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self.repopulate_box(self.dataset_box, datasets, random)
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# Select a random speaker
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if level <= 1:
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speakers_root = datasets_root.joinpath(self.current_dataset_name)
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speaker_names = [d.stem for d in speakers_root.glob("*") if d.is_dir()]
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self.repopulate_box(self.speaker_box, speaker_names, random)
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# Select a random utterance
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if level <= 2:
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utterances_root = datasets_root.joinpath(
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self.current_dataset_name,
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self.current_speaker_name
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)
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utterances = []
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for extension in ['mp3', 'flac', 'wav', 'm4a']:
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utterances.extend(Path(utterances_root).glob("**/*.%s" % extension))
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utterances = [fpath.relative_to(utterances_root) for fpath in utterances]
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self.repopulate_box(self.utterance_box, utterances, random)
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def browser_select_next(self):
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index = (self.utterance_box.currentIndex() + 1) % len(self.utterance_box)
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self.utterance_box.setCurrentIndex(index)
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@property
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def current_encoder_fpath(self):
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return self.encoder_box.itemData(self.encoder_box.currentIndex())
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@property
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def current_synthesizer_fpath(self):
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return self.synthesizer_box.itemData(self.synthesizer_box.currentIndex())
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@property
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def current_vocoder_fpath(self):
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return self.vocoder_box.itemData(self.vocoder_box.currentIndex())
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@property
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def current_extractor_fpath(self):
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return self.extractor_box.itemData(self.extractor_box.currentIndex())
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@property
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def current_convertor_fpath(self):
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return self.convertor_box.itemData(self.convertor_box.currentIndex())
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def populate_models(self, encoder_models_dir: Path, synthesizer_models_dir: Path,
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vocoder_models_dir: Path, extractor_models_dir: Path, convertor_models_dir: Path, vc_mode: bool):
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# Encoder
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encoder_fpaths = list(encoder_models_dir.glob("*.pt"))
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if len(encoder_fpaths) == 0:
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raise Exception("No encoder models found in %s" % encoder_models_dir)
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self.repopulate_box(self.encoder_box, [(f.stem, f) for f in encoder_fpaths])
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if vc_mode:
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# Extractor
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extractor_fpaths = list(extractor_models_dir.glob("*.pt"))
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if len(extractor_fpaths) == 0:
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self.log("No extractor models found in %s" % extractor_fpaths)
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self.repopulate_box(self.extractor_box, [(f.stem, f) for f in extractor_fpaths])
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# Convertor
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convertor_fpaths = list(convertor_models_dir.glob("*.pth"))
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if len(convertor_fpaths) == 0:
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self.log("No convertor models found in %s" % convertor_fpaths)
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self.repopulate_box(self.convertor_box, [(f.stem, f) for f in convertor_fpaths])
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else:
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# Synthesizer
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synthesizer_fpaths = list(synthesizer_models_dir.glob("**/*.pt"))
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if len(synthesizer_fpaths) == 0:
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raise Exception("No synthesizer models found in %s" % synthesizer_models_dir)
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self.repopulate_box(self.synthesizer_box, [(f.stem, f) for f in synthesizer_fpaths])
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# Vocoder
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vocoder_fpaths = list(vocoder_models_dir.glob("**/*.pt"))
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vocoder_items = [(f.stem, f) for f in vocoder_fpaths] + [("Griffin-Lim", None)]
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self.repopulate_box(self.vocoder_box, vocoder_items)
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@property
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def selected_utterance(self):
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return self.utterance_history.itemData(self.utterance_history.currentIndex())
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def register_utterance(self, utterance: Utterance, vc_mode):
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self.utterance_history.blockSignals(True)
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self.utterance_history.insertItem(0, utterance.name, utterance)
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self.utterance_history.setCurrentIndex(0)
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self.utterance_history.blockSignals(False)
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if len(self.utterance_history) > self.max_saved_utterances:
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self.utterance_history.removeItem(self.max_saved_utterances)
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self.play_button.setDisabled(False)
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if vc_mode:
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self.convert_button.setDisabled(False)
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else:
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self.generate_button.setDisabled(False)
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self.synthesize_button.setDisabled(False)
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def log(self, line, mode="newline"):
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if mode == "newline":
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self.logs.append(line)
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if len(self.logs) > self.max_log_lines:
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del self.logs[0]
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elif mode == "append":
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self.logs[-1] += line
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elif mode == "overwrite":
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self.logs[-1] = line
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log_text = '\n'.join(self.logs)
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self.log_window.setText(log_text)
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self.app.processEvents()
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def set_loading(self, value, maximum=1):
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self.loading_bar.setValue(value * 100)
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self.loading_bar.setMaximum(maximum * 100)
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self.loading_bar.setTextVisible(value != 0)
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self.app.processEvents()
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def populate_gen_options(self, seed, trim_silences):
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if seed is not None:
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self.random_seed_checkbox.setChecked(True)
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self.seed_textbox.setText(str(seed))
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self.seed_textbox.setEnabled(True)
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else:
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self.random_seed_checkbox.setChecked(False)
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self.seed_textbox.setText(str(0))
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self.seed_textbox.setEnabled(False)
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if not trim_silences:
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self.trim_silences_checkbox.setChecked(False)
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self.trim_silences_checkbox.setDisabled(True)
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def update_seed_textbox(self):
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if self.random_seed_checkbox.isChecked():
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self.seed_textbox.setEnabled(True)
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else:
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self.seed_textbox.setEnabled(False)
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def reset_interface(self, vc_mode):
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self.draw_embed(None, None, "current")
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self.draw_embed(None, None, "generated")
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self.draw_spec(None, "current")
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self.draw_spec(None, "generated")
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self.draw_umap_projections(set())
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self.set_loading(0)
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self.play_button.setDisabled(True)
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if vc_mode:
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self.convert_button.setDisabled(True)
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else:
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self.generate_button.setDisabled(True)
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self.synthesize_button.setDisabled(True)
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self.vocode_button.setDisabled(True)
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self.replay_wav_button.setDisabled(True)
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self.export_wav_button.setDisabled(True)
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[self.log("") for _ in range(self.max_log_lines)]
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def __init__(self, vc_mode):
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## Initialize the application
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self.app = QApplication(sys.argv)
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super().__init__(None)
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self.setWindowTitle("MockingBird GUI")
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self.setWindowIcon(QtGui.QIcon('toolbox\\assets\\mb.png'))
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self.setWindowFlag(Qt.WindowMinimizeButtonHint, True)
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self.setWindowFlag(Qt.WindowMaximizeButtonHint, True)
|
|
|
|
|
|
## Main layouts
|
|
# Root
|
|
root_layout = QGridLayout()
|
|
self.setLayout(root_layout)
|
|
|
|
# Browser
|
|
browser_layout = QGridLayout()
|
|
root_layout.addLayout(browser_layout, 0, 0, 1, 8)
|
|
|
|
# Generation
|
|
gen_layout = QVBoxLayout()
|
|
root_layout.addLayout(gen_layout, 0, 8)
|
|
|
|
# Visualizations
|
|
vis_layout = QVBoxLayout()
|
|
root_layout.addLayout(vis_layout, 1, 0, 2, 8)
|
|
|
|
# Output
|
|
output_layout = QGridLayout()
|
|
vis_layout.addLayout(output_layout, 0)
|
|
|
|
# Projections
|
|
self.projections_layout = QVBoxLayout()
|
|
root_layout.addLayout(self.projections_layout, 1, 8, 2, 2)
|
|
|
|
## Projections
|
|
# UMap
|
|
fig, self.umap_ax = plt.subplots(figsize=(3, 3), facecolor="#F0F0F0")
|
|
fig.subplots_adjust(left=0.02, bottom=0.02, right=0.98, top=0.98)
|
|
self.projections_layout.addWidget(FigureCanvas(fig))
|
|
self.umap_hot = False
|
|
self.clear_button = QPushButton("Clear")
|
|
self.projections_layout.addWidget(self.clear_button)
|
|
|
|
|
|
## Browser
|
|
# Dataset, speaker and utterance selection
|
|
i = 0
|
|
|
|
source_groupbox = QGroupBox('Source(源音频)')
|
|
source_layout = QGridLayout()
|
|
source_groupbox.setLayout(source_layout)
|
|
browser_layout.addWidget(source_groupbox, i, 0, 1, 5)
|
|
|
|
self.dataset_box = QComboBox()
|
|
source_layout.addWidget(QLabel("Dataset(数据集):"), i, 0)
|
|
source_layout.addWidget(self.dataset_box, i, 1)
|
|
self.random_dataset_button = QPushButton("Random")
|
|
source_layout.addWidget(self.random_dataset_button, i, 2)
|
|
i += 1
|
|
self.speaker_box = QComboBox()
|
|
source_layout.addWidget(QLabel("Speaker(说话者)"), i, 0)
|
|
source_layout.addWidget(self.speaker_box, i, 1)
|
|
self.random_speaker_button = QPushButton("Random")
|
|
source_layout.addWidget(self.random_speaker_button, i, 2)
|
|
i += 1
|
|
self.utterance_box = QComboBox()
|
|
source_layout.addWidget(QLabel("Utterance(音频):"), i, 0)
|
|
source_layout.addWidget(self.utterance_box, i, 1)
|
|
self.random_utterance_button = QPushButton("Random")
|
|
source_layout.addWidget(self.random_utterance_button, i, 2)
|
|
|
|
i += 1
|
|
source_layout.addWidget(QLabel("<b>Use(使用):</b>"), i, 0)
|
|
self.browser_load_button = QPushButton("Load Above(加载上面)")
|
|
source_layout.addWidget(self.browser_load_button, i, 1, 1, 2)
|
|
self.auto_next_checkbox = QCheckBox("Auto select next")
|
|
self.auto_next_checkbox.setChecked(True)
|
|
source_layout.addWidget(self.auto_next_checkbox, i+1, 1)
|
|
self.browser_browse_button = QPushButton("Browse(打开本地)")
|
|
source_layout.addWidget(self.browser_browse_button, i, 3)
|
|
self.record_button = QPushButton("Record(录音)")
|
|
source_layout.addWidget(self.record_button, i+1, 3)
|
|
|
|
i += 2
|
|
# Utterance box
|
|
browser_layout.addWidget(QLabel("<b>Current(当前):</b>"), i, 0)
|
|
self.utterance_history = QComboBox()
|
|
browser_layout.addWidget(self.utterance_history, i, 1)
|
|
self.play_button = QPushButton("Play(播放)")
|
|
browser_layout.addWidget(self.play_button, i, 2)
|
|
self.stop_button = QPushButton("Stop(暂停)")
|
|
browser_layout.addWidget(self.stop_button, i, 3)
|
|
if vc_mode:
|
|
self.load_soruce_button = QPushButton("Select(选择为被转换的语音输入)")
|
|
browser_layout.addWidget(self.load_soruce_button, i, 4)
|
|
|
|
i += 1
|
|
model_groupbox = QGroupBox('Models(模型选择)')
|
|
model_layout = QHBoxLayout()
|
|
model_groupbox.setLayout(model_layout)
|
|
browser_layout.addWidget(model_groupbox, i, 0, 2, 5)
|
|
|
|
# Model and audio output selection
|
|
self.encoder_box = QComboBox()
|
|
model_layout.addWidget(QLabel("Encoder:"))
|
|
model_layout.addWidget(self.encoder_box)
|
|
self.synthesizer_box = QComboBox()
|
|
if vc_mode:
|
|
self.extractor_box = QComboBox()
|
|
model_layout.addWidget(QLabel("Extractor:"))
|
|
model_layout.addWidget(self.extractor_box)
|
|
self.convertor_box = QComboBox()
|
|
model_layout.addWidget(QLabel("Convertor:"))
|
|
model_layout.addWidget(self.convertor_box)
|
|
else:
|
|
model_layout.addWidget(QLabel("Synthesizer:"))
|
|
model_layout.addWidget(self.synthesizer_box)
|
|
self.vocoder_box = QComboBox()
|
|
model_layout.addWidget(QLabel("Vocoder:"))
|
|
model_layout.addWidget(self.vocoder_box)
|
|
|
|
#Replay & Save Audio
|
|
i = 0
|
|
output_layout.addWidget(QLabel("<b>Toolbox Output:</b>"), i, 0)
|
|
self.waves_cb = QComboBox()
|
|
self.waves_cb_model = QStringListModel()
|
|
self.waves_cb.setModel(self.waves_cb_model)
|
|
self.waves_cb.setToolTip("Select one of the last generated waves in this section for replaying or exporting")
|
|
output_layout.addWidget(self.waves_cb, i, 1)
|
|
self.replay_wav_button = QPushButton("Replay")
|
|
self.replay_wav_button.setToolTip("Replay last generated vocoder")
|
|
output_layout.addWidget(self.replay_wav_button, i, 2)
|
|
self.export_wav_button = QPushButton("Export")
|
|
self.export_wav_button.setToolTip("Save last generated vocoder audio in filesystem as a wav file")
|
|
output_layout.addWidget(self.export_wav_button, i, 3)
|
|
self.audio_out_devices_cb=QComboBox()
|
|
i += 1
|
|
output_layout.addWidget(QLabel("<b>Audio Output</b>"), i, 0)
|
|
output_layout.addWidget(self.audio_out_devices_cb, i, 1)
|
|
|
|
## Embed & spectrograms
|
|
vis_layout.addStretch()
|
|
# TODO: add spectrograms for source
|
|
gridspec_kw = {"width_ratios": [1, 4]}
|
|
fig, self.current_ax = plt.subplots(1, 2, figsize=(10, 2.25), facecolor="#F0F0F0",
|
|
gridspec_kw=gridspec_kw)
|
|
fig.subplots_adjust(left=0, bottom=0.1, right=1, top=0.8)
|
|
vis_layout.addWidget(FigureCanvas(fig))
|
|
|
|
fig, self.gen_ax = plt.subplots(1, 2, figsize=(10, 2.25), facecolor="#F0F0F0",
|
|
gridspec_kw=gridspec_kw)
|
|
fig.subplots_adjust(left=0, bottom=0.1, right=1, top=0.8)
|
|
vis_layout.addWidget(FigureCanvas(fig))
|
|
|
|
for ax in self.current_ax.tolist() + self.gen_ax.tolist():
|
|
ax.set_facecolor("#F0F0F0")
|
|
for side in ["top", "right", "bottom", "left"]:
|
|
ax.spines[side].set_visible(False)
|
|
|
|
## Generation
|
|
self.text_prompt = QPlainTextEdit(default_text)
|
|
gen_layout.addWidget(self.text_prompt, stretch=1)
|
|
|
|
if vc_mode:
|
|
layout = QHBoxLayout()
|
|
self.convert_button = QPushButton("Extract and Convert")
|
|
layout.addWidget(self.convert_button)
|
|
gen_layout.addLayout(layout)
|
|
else:
|
|
self.generate_button = QPushButton("Synthesize and vocode")
|
|
gen_layout.addWidget(self.generate_button)
|
|
layout = QHBoxLayout()
|
|
self.synthesize_button = QPushButton("Synthesize only")
|
|
layout.addWidget(self.synthesize_button)
|
|
|
|
self.vocode_button = QPushButton("Vocode only")
|
|
layout.addWidget(self.vocode_button)
|
|
gen_layout.addLayout(layout)
|
|
|
|
|
|
layout_seed = QGridLayout()
|
|
self.random_seed_checkbox = QCheckBox("Random seed:")
|
|
self.random_seed_checkbox.setToolTip("When checked, makes the synthesizer and vocoder deterministic.")
|
|
layout_seed.addWidget(self.random_seed_checkbox, 0, 0)
|
|
self.seed_textbox = QLineEdit()
|
|
self.seed_textbox.setMaximumWidth(80)
|
|
layout_seed.addWidget(self.seed_textbox, 0, 1)
|
|
self.trim_silences_checkbox = QCheckBox("Enhance vocoder output")
|
|
self.trim_silences_checkbox.setToolTip("When checked, trims excess silence in vocoder output."
|
|
" This feature requires `webrtcvad` to be installed.")
|
|
layout_seed.addWidget(self.trim_silences_checkbox, 0, 2, 1, 2)
|
|
self.style_slider = QSlider(Qt.Horizontal)
|
|
self.style_slider.setTickInterval(1)
|
|
self.style_slider.setFocusPolicy(Qt.NoFocus)
|
|
self.style_slider.setSingleStep(1)
|
|
self.style_slider.setRange(-1, 9)
|
|
self.style_value_label = QLabel("-1")
|
|
self.style_slider.setValue(-1)
|
|
layout_seed.addWidget(QLabel("Style:"), 1, 0)
|
|
|
|
self.style_slider.valueChanged.connect(lambda s: self.style_value_label.setNum(s))
|
|
layout_seed.addWidget(self.style_value_label, 1, 1)
|
|
layout_seed.addWidget(self.style_slider, 1, 3)
|
|
|
|
self.token_slider = QSlider(Qt.Horizontal)
|
|
self.token_slider.setTickInterval(1)
|
|
self.token_slider.setFocusPolicy(Qt.NoFocus)
|
|
self.token_slider.setSingleStep(1)
|
|
self.token_slider.setRange(3, 9)
|
|
self.token_value_label = QLabel("5")
|
|
self.token_slider.setValue(4)
|
|
layout_seed.addWidget(QLabel("Accuracy(精度):"), 2, 0)
|
|
|
|
self.token_slider.valueChanged.connect(lambda s: self.token_value_label.setNum(s))
|
|
layout_seed.addWidget(self.token_value_label, 2, 1)
|
|
layout_seed.addWidget(self.token_slider, 2, 3)
|
|
|
|
self.length_slider = QSlider(Qt.Horizontal)
|
|
self.length_slider.setTickInterval(1)
|
|
self.length_slider.setFocusPolicy(Qt.NoFocus)
|
|
self.length_slider.setSingleStep(1)
|
|
self.length_slider.setRange(1, 10)
|
|
self.length_value_label = QLabel("2")
|
|
self.length_slider.setValue(2)
|
|
layout_seed.addWidget(QLabel("MaxLength(最大句长):"), 3, 0)
|
|
|
|
self.length_slider.valueChanged.connect(lambda s: self.length_value_label.setNum(s))
|
|
layout_seed.addWidget(self.length_value_label, 3, 1)
|
|
layout_seed.addWidget(self.length_slider, 3, 3)
|
|
|
|
gen_layout.addLayout(layout_seed)
|
|
|
|
self.loading_bar = QProgressBar()
|
|
gen_layout.addWidget(self.loading_bar)
|
|
|
|
self.log_window = QLabel()
|
|
self.log_window.setAlignment(Qt.AlignBottom | Qt.AlignLeft)
|
|
gen_layout.addWidget(self.log_window)
|
|
self.logs = []
|
|
gen_layout.addStretch()
|
|
|
|
|
|
## Set the size of the window and of the elements
|
|
max_size = QDesktopWidget().availableGeometry(self).size() * 0.5
|
|
self.resize(max_size)
|
|
|
|
## Finalize the display
|
|
self.reset_interface(vc_mode)
|
|
self.show()
|
|
|
|
def start(self):
|
|
self.app.exec_()
|