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• pyqt5 gui dependent on ffmpeg compiled with pyinstaller doesn't run on other machines ?

  19 octobre 2022, par Soren

  I am trying to create a simple Pyqt5 GUI for Windows 10 that uses OpenAI's model Whisper to transcribe a sound file and outputting the results in an Excel-file. It works on my own computer where I have installed the necessary dependencies for Whisper as stated on their github i.e. FFMEG. I provide a minimal example of my code below :

  


  # Import library
import whisper
import os
from PyQt5 import QtCore, QtGui, QtWidgets
import pandas as pd
import xlsxwriter


class Ui_Dialog(QtWidgets.QDialog):
    
    
    # Define functions to use in GUI
   
    # Define function for selecting input files
    def browsefiles(self, Dialog):
      
       
       # Make Dialog box and save files into tuple of paths
       files = QtWidgets.QFileDialog().getOpenFileNames(self, "Select soundfiles", os.getcwd(), "lyd(*mp2 *.mp3 *.mp4 *.m4a *wma *wav)")
       
       self.liste = []
       for url in range(len(files[0])):
           self.liste.append(files[0][url])   

    
    def model_load(self, Dialog):
               
        # Load picked model
        self.model = whisper.load_model(r'C:\Users\Søren\Downloads\Whisper_gui\models' + "\\" + self.combo_modelSize.currentText() + ".pt") ##the path is set to where the models are on the other machine
        
    
    def run(self, Dialog):
                
        # Make list for sound files
        liste_df = []
        
        
        # Running loop for interpreting and encoding sound files
        for url in range(len(self.liste)):
                          
            # Make dataframe
            df = pd.DataFrame(columns=["filename", "start", "end", "text"])
            
            # Run model
            result = self.model.transcribe(self.liste[url])
                            
            # Extract results
            for i in range(len(result["segments"])):
                start = result["segments"][i]["start"]
                end = result["segments"][i]["end"]
                text = result["segments"][i]["text"]
                
                df = df.append({"filename": self.liste[url].split("/")[-1],
                            "start": start, 
                            "end": end, 
                            "text": text}, ignore_index=True)
            
            # Add detected language to dataframe
            df["sprog"] = result["language"]
            
            
            liste_df.append(df)
        
        
        
        # Make excel output
        
        # Concatenate list of dfs
        dataframe = pd.concat(liste_df)
        
        
        # Create a Pandas Excel writer using XlsxWriter as the engine.
        writer = pd.ExcelWriter(self.liste[0].split(".")[0] + '_OUTPUT.xlsx', engine='xlsxwriter')
        writer_wrap_format = writer.book.add_format({"text_wrap": True, 'num_format': '@'})


        # Write the dataframe data to XlsxWriter. Turn off the default header and
        # index and skip one row to allow us to insert a user defined header.
        dataframe.to_excel(writer, sheet_name="Output", startrow=1, header=False, index=False)

        # Get the xlsxwriter workbook and worksheet objects.
        #workbook = writer.book
        worksheet = writer.sheets["Output"]

        # Get the dimensions of the dataframe.
        (max_row, max_col) = dataframe.shape

        # Create a list of column headers, to use in add_table().
        column_settings = [{'header': column} for column in dataframe.columns]

        # Add the Excel table structure. Pandas will add the data.
        worksheet.add_table(0, 0, max_row, max_col - 1, {'columns': column_settings})

        # Make the columns wider for clarity.
        worksheet.set_column(0, max_col - 1, 12)
        
        in_col_no = xlsxwriter.utility.xl_col_to_name(dataframe.columns.get_loc("text"))
        
        worksheet.set_column(in_col_no + ":" + in_col_no, 30, writer_wrap_format)

        # Close the Pandas Excel writer and output the Excel file.
        writer.save()
        writer.close()
    
    
    ## Design setup
    
    def setupUi(self, Dialog):
        Dialog.setObjectName("Dialog")
        Dialog.resize(730, 400)
        
        self.select_files = QtWidgets.QPushButton(Dialog)
        self.select_files.setGeometry(QtCore.QRect(40, 62, 81, 31))
        font = QtGui.QFont()
        font.setPointSize(6)
        self.select_files.setFont(font)
        self.select_files.setObjectName("select_files")
        
    
               
        
        self.combo_modelSize = QtWidgets.QComboBox(Dialog)
        self.combo_modelSize.setGeometry(QtCore.QRect(40, 131, 100, 21))
        font = QtGui.QFont()
        font.setPointSize(6)
        self.combo_modelSize.setFont(font)
        self.combo_modelSize.setObjectName("combo_modelSize")
               
        
        self.runButton = QtWidgets.QPushButton(Dialog)
        self.runButton.setGeometry(QtCore.QRect(40, 289, 71, 21))
        font = QtGui.QFont()
        font.setPointSize(6)
        self.runButton.setFont(font)
        self.runButton.setObjectName("runButton")
        
        
       

        self.retranslateUi(Dialog)
        QtCore.QMetaObject.connectSlotsByName(Dialog)
        
        
        
        modelSize_options = ['Chose model', 'tiny', 'base', 'small', 'medium', 'large']
        self.combo_modelSize.addItems(modelSize_options)
        
        # Do an action!
        self.select_files.clicked.connect(self.browsefiles)
        self.combo_modelSize.currentIndexChanged.connect(self.model_load)
        self.runButton.clicked.connect(self.run)
        
        
        
    

    def retranslateUi(self, Dialog):
        _translate = QtCore.QCoreApplication.translate
        Dialog.setWindowTitle(_translate("Dialog", "Dialog"))
        self.runButton.setText(_translate("Dialog", "Go!"))
        self.select_files.setText(_translate("Dialog", "Select"))


if __name__ == "__main__":
    import sys
    app = QtWidgets.QApplication(sys.argv)
    Dialog = QtWidgets.QDialog()
    ui = Ui_Dialog()
    ui.setupUi(Dialog)
    Dialog.show()
    sys.exit(app.exec_())


  


  I compile this app with pyinstaller using the following code. I had some issues to begin with so I found other with similar problems and ended up with this :

  


  pyinstaller --onedir --hidden-import=pytorch --collect-data torch --copy-metadata torch --copy-metadata tqdm --copy-metadata tokenizers --copy-metadata importlib_metadata --hidden-import="sklearn.utils._cython_blas" --hidden-import="sklearn.neighbors.typedefs" --hidden-import="sklearn.neighbors.quad_tree" --hidden-import="sklearn.tree" --hidden-import="sklearn.tree._utils" --copy-metadata regex --copy-metadata requests --copy-metadata packaging --copy-metadata filelock --copy-metadata numpy --add-data "./ffmpeg/*;./ffmpeg/" --hidden-import=whisper --copy-metadata whisper --collect-data whisper minimal_example_whisper.py

  


  When I take the outputtet dist directory and try to run the app on another Windows machine without FFMPEG installed (or Whisper or any other things), I get the following error from the terminal as I push the "run" button in the app (otherwise the app does run).

  


  C:\Users\Søren>"G:\minimal_example_whisper\minimal_example_whisper.exe"
whisper\transcribe.py:70: UserWarning: FP16 is not supported on CPU; using FP32 instead
Traceback (most recent call last):
  File "minimal_example_whisper.py", line 45, in run
  File "whisper\transcribe.py", line 76, in transcribe
  File "whisper\audio.py", line 111, in log_mel_spectrogram
  File "whisper\audio.py", line 42, in load_audio
  File "ffmpeg\_run.py", line 313, in run
  File "ffmpeg\_run.py", line 284, in run_async
  File "subprocess.py", line 951, in __init__
  File "subprocess.py", line 1420, in _execute_child
FileNotFoundError: [WinError 2] Den angivne fil blev ikke fundet


  


  I suspect this has something to do with FFMPEG not being installed on the other machines system ? Does anyone have an automatic solution for this when compiling the app or can it simply only run on machines that has FFMPEG installed ?

  


  Thanks in advance !

  


• ffmpeg works at command line but I got this error when I use it in nodejs app :

  15 avril 2023, par Ibrahim Ashour

  This is the code :

  


  import fs from 'fs';
import googleTTS from 'google-tts-api';
import https from 'https';
import { exec } from 'child_process';

async function convertTextToVoice(text, fileName) {
  const outputFile = `./audios/${fileName}.mp3`;

  const words = text.split(' ');
  const chunks = [];
  let chunk = '';

  for (const word of words) {
    if (chunk.length + word.length < 200) {
      chunk += ' ' + word;
    } else {
      chunks.push(chunk.trim());
      chunk = word;
    }
  }

  chunks.push(chunk.trim());

  for (let i = 0; i < chunks.length; i++) {
    const chunkFile = `./audios/${fileName}-chunk${i}.mp3`;
    const url = await googleTTS.getAudioUrl(chunks[i], {
      lang: 'ar',
      slow: false,
      host: 'https://translate.google.com',
    });


    try {
      const file = await fs.createWriteStream(chunkFile);
      https.get(url, response => {
        response.pipe(file);
        file.on('finish', () => {
          file.close();
          console.log(`Chunk ${i} created successfully`);
        });
      }).on('error', error => {
        console.error(`Error downloading chunk ${i}: ${error}`);
      });
    } catch (error) {
      console.error(error);
    }
  }

  const chunkFiles = chunks.map((chunk, i) => `./audios/${fileName}-chunk${i}.mp3`);

  // Use ffmpeg to merge the audio files
  const concatCommand = `ffmpeg -i "concat:${chunkFiles.join('|')}" -acodec copy ${outputFile}`;
  try {
    await new Promise((resolve, reject) => {
      exec(concatCommand, (error, stdout, stderr) => {
        if (error) {
          console.error(`Error executing ffmpeg command: ${error}`);
          reject(error);
        } else {
          console.log(`Audio file ${outputFile} created successfully`);
          resolve();
        }
      });
    });

    for (const chunkFile of chunkFiles) {
      await fs.promises.unlink(chunkFile);
      console.log(`${chunkFile} deleted successfully`);
    }
  } catch (error) {
    console.error(error);
  }
}


  


  This is the Error :
./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3
ffmpeg -i "concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3" -acodec copy ./audios/تجربة.mp3
Error executing ffmpeg command : Error : Command failed : ffmpeg -i "concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3" -acodec copy ./audios/تجربة.mp3
ffmpeg version 2023-02-04-git-bdc76f467f-full_build-www.gyan.dev Copyright (c) 2000-2023 the FFmpeg developers
built with gcc 12.2.0 (Rev10, Built by MSYS2 project)
configuration : —enable-gpl —enable-version3 —enable-static —disable-w32threads —disable-autodetect —enable-fontconfig —enable-iconv —enable-gnutls —enable-libxml2 —enable-gmp —enable-bzlib —enable-lzma —enable-libsnappy —enable-zlib —enable-librist —enable-libsrt —enable-libssh —enable-libzmq —enable-avisynth —enable-libbluray —enable-libcaca —enable-sdl2 —enable-libaribb24 —enable-libdav1d —enable-libdavs2 —enable-libuavs3d —enable-libzvbi —enable-librav1e —enable-libsvtav1 —enable-libwebp —enable-libx264 —enable-libx265 —enable-libxavs2 —enable-libxvid —enable-libaom —enable-libjxl —enable-libopenjpeg —enable-libvpx —enable-mediafoundation —enable-libass —enable-frei0r —enable-libfreetype —enable-libfribidi —enable-liblensfun —enable-libvidstab —enable-libvmaf —enable-libzimg —enable-amf —enable-cuda-llvm —enable-cuvid —enable-ffnvcodec —enable-nvdec —enable-nvenc —enable-d3d11va —enable-dxva2 —enable-libvpl —enable-libshaderc —enable-vulkan —enable-libplacebo —enable-opencl —enable-libcdio —enable-libgme —enable-libmodplug —enable-libopenmpt —enable-libopencore-amrwb —enable-libmp3lame —enable-libshine —enable-libtheora —enable-libtwolame —enable-libvo-amrwbenc —enable-libilbc —enable-libgsm —enable-libopencore-amrnb —enable-libopus —enable-libspeex —enable-libvorbis —enable-ladspa —enable-libbs2b —enable-libflite —enable-libmysofa —enable-librubberband —enable-libsoxr —enable-chromaprint
libavutil 57. 44.100 / 57. 44.100
libavcodec 59. 63.100 / 59. 63.100
libavformat 59. 38.100 / 59. 38.100
libavdevice 59. 8.101 / 59. 8.101
libavfilter 8. 56.100 / 8. 56.100
libswscale 6. 8.112 / 6. 8.112
libswresample 4. 9.100 / 4. 9.100
libpostproc 56. 7.100 / 56. 7.100
[mp3 @ 00000177df48a1c0] Format mp3 detected only with low score of 1, misdetection possible !
[mp3 @ 00000177df48a1c0] Failed to read frame size : Could not seek to 1026.
concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3 : Invalid argument

  


  Error : Command failed : ffmpeg -i "concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3" -acodec copy ./audios/تجربة.mp3
ffmpeg version 2023-02-04-git-bdc76f467f-full_build-www.gyan.dev Copyright (c) 2000-2023 the FFmpeg developers
built with gcc 12.2.0 (Rev10, Built by MSYS2 project)
configuration : —enable-gpl —enable-version3 —enable-static —disable-w32threads —disable-autodetect —enable-fontconfig —enable-iconv —enable-gnutls —enable-libxml2 —enable-gmp —enable-bzlib —enable-lzma —enable-libsnappy —enable-zlib —enable-librist —enable-libsrt —enable-libssh —enable-libzmq —enable-avisynth —enable-libbluray —enable-libcaca —enable-sdl2 —enable-libaribb24 —enable-libdav1d —enable-libdavs2 —enable-libuavs3d —enable-libzvbi —enable-librav1e —enable-libsvtav1 —enable-libwebp —enable-libx264 —enable-libx265 —enable-libxavs2 —enable-libxvid —enable-libaom —enable-libjxl —enable-libopenjpeg —enable-libvpx —enable-mediafoundation —enable-libass —enable-frei0r —enable-libfreetype —enable-libfribidi —enable-liblensfun —enable-libvidstab —enable-libvmaf —enable-libzimg —enable-amf —enable-cuda-llvm —enable-cuvid —enable-ffnvcodec —enable-nvdec —enable-nvenc —enable-d3d11va —enable-dxva2 —enable-libvpl —enable-libshaderc —enable-vulkan —enable-libplacebo —enable-opencl —enable-libcdio —enable-libgme —enable-libmodplug —enable-libopenmpt —enable-libopencore-amrwb —enable-libmp3lame —enable-libshine —enable-libtheora —enable-libtwolame —enable-libvo-amrwbenc —enable-libilbc —enable-libgsm —enable-libopencore-amrnb —enable-libopus —enable-libspeex —enable-libvorbis —enable-ladspa —enable-libbs2b —enable-libflite —enable-libmysofa —enable-librubberband —enable-libsoxr —enable-chromaprint
libavutil 57. 44.100 / 57. 44.100
libavcodec 59. 63.100 / 59. 63.100
libavformat 59. 38.100 / 59. 38.100
libavdevice 59. 8.101 / 59. 8.101
libavfilter 8. 56.100 / 8. 56.100
libswscale 6. 8.112 / 6. 8.112
libswresample 4. 9.100 / 4. 9.100
libpostproc 56. 7.100 / 56. 7.100
[mp3 @ 00000177df48a1c0] Format mp3 detected only with low score of 1, misdetection possible !
[mp3 @ 00000177df48a1c0] Failed to read frame size : Could not seek to 1026.
concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3 : Invalid argument

  


  at ChildProcess.exithandler (node:child_process:419:12)
at ChildProcess.emit (node:events:513:28)
at maybeClose (node:internal/child_process:1091:16)
at ChildProcess._handle.onexit (node:internal/child_process:302:5) {


  


  code : 1,
killed : false,
signal : null,
cmd : 'ffmpeg -i "concat :./audios/تجربة-chunk0.mp3|./audios/تجربة-chunk1.mp3" -acodec copy ./audios/تجربة.mp3'
}
Chunk 1 created successfully
Chunk 0 created successfully

  


  I expected the command to work in the nodejs app like in the command line

  


• Data Privacy Day 2021 : Five ways to embrace privacy into your business

  27 janvier 2021, par Matomo Core Team — Community, Privacy

  Welcome to Data Privacy Day 2021 !

  This year we are excited to announce that we are participating as a #PrivacyAware Champion for DPD21 through the National Cyber Security Alliance. This means that on this significant day we are in partnership with hundreds of other organisations and businesses to share a unified message that empowers individuals to “Own Your Privacy” and for organisations to “Respect Privacy.”

  "Last year dawned a new era in the way many businesses operate from a traditional office work setting to a remote working from home environment for employees. This now means it’s more important than ever for your employees to understand how to take ownership of their privacy when working online."

  As a Data Privacy Day #PrivacyAware Champion we would like to provide some practical tips and share examples of how the Matomo team helps employees be privacy aware.

  

  Five ways to embrace privacy into your business

  1. Create a privacy aware culture within your business

  • Get leadership involved.
  • Appoint privacy ambassadors within your team. 
  • Create a privacy awareness campaign where you educate employees on your company privacy policy. 
  • Share messages about privacy around the office/or in meetings online, on internal message boards, in company newsletters, or emails. 
  • Teach new employees their role in your privacy culture and reinforce throughout their career.

  2. Organise privacy awareness training for your employees

  • Invite outside speakers to talk to employees about why privacy matters. 
  • Engage staff by asking them to consider how privacy and data security applies to the work they do on a daily basis.
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  3. Help employees manage their individual privacy

  • Better security and privacy behaviours at home will translate to better security and privacy practices at work. 
  • Teach employees how to update their privacy and security settings on personal accounts.
  • Use NCSA’s privacy settings page to help them get started

  4. Add privacy to the employee’s toolbox

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  Want to find out more about data privacy download your free DPD 2021 Champion Toolkit and read our post on “Why is privacy important”.

  Team Matomo

  2021 Data Privacy Day Toolkit

  Your guide to Data Privacy Day, January 28, 2021

  Free Download