deepfake-ecg-generator-plus

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# ==========================================================================
#         ____                   __       _          _____ ____ ____
#        |  _ \  ___  ___ _ __  / _| __ _| | _____  | ____/ ___/ ___|
#        | | | |/ _ \/ _ \ '_ \| |_ / _` | |/ / _ \ |  _|| |  | |  _
#        | |_| |  __/  __/ |_) |  _| (_| |   <  __/ | |__| |__| |_| |
#        |____/ \___|\___| .__/|_|  \__,_|_|\_\___| |_____\____\____|
#                        |_|
#
#                       --- Deepfake ECG Generator ---
#                https://github.com/vlbthambawita/deepfake-ecg
# ==========================================================================
#
# DeepfakeECG GUI Application
# Copyright (C) 2023-2025 by Vajira Thambawita
# Copyright (C) 2025 by Thomas Dreibholz
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.

# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
# Contact:
# * Vajira Thambawita <[email protected]>
# * Thomas Dreibholz <[email protected]>

import datetime
import deepfakeecg
import ecg_plot
import gradio
import io
import matplotlib.pyplot as plt
import matplotlib.ticker
import numpy
import pathlib
import random
import sys
import tempfile
import threading
import torch
import typing
import PIL


TempDirectory = None
Sessions      = {}


# ###### Print log message ##################################################
def log(logstring):
   print(('\x1b[34m' + datetime.datetime.now().strftime('%Y-%m-%dT%H:%M:%S') +
          ': ' + logstring + '\x1b[0m'));


# ###### DeepFakeECG Plus Session (session with web browser) ################
class Session:

   # ###### Constructor #####################################################
   def __init__(self):
      self.Lock          = threading.Lock()
      self.Counter       = 0
      self.Selected      = 0
      self.Results       = None
      self.Type          = None
      self.TempDirectory = tempfile.TemporaryDirectory(dir = TempDirectory.name)
      log(f'Prepared temporary directory {self.TempDirectory.name}')

   # ###### Destructor ######################################################
   def __del__(self):
      log(f'Cleaning up temporary directory {self.TempDirectory.name}')
      self.TempDirectory.cleanup()

   # ###### Increment counter ###############################################
   def increment(self):
      with self.lock:
         self.counter += 1
         return self.counter

   # ###### Increment counter ###############################################
   def increment(self):
      with self.lock:
         self.counter += 1
         return self.counter


# ###### Initialize a new session ###########################################
def initializeSession(request: gradio.Request):
   Sessions[request.session_hash] = Session()
   log(f'Session "{request.session_hash}" initialized')


# ###### Clean up a session #################################################
def cleanUpSession(request: gradio.Request):
   if request.session_hash in Sessions:
      del instances[request.session_hash]
   log(f'Session "{request.session_hash}" cleaned up')


# ###### Increment counter in session #######################################
def incrementCounter(request: gradio.Request):
   if request.session_hash in Sessions:
      instance = Sessions[request.session_hash]
      return instance.increment()
   log(f'ERROR: Session "{request.session_hash}" is not initialized!')



# ###### Generate ECGs ######################################################
def predict(numberOfECGs:         int = 1,
            # ecgLengthInSeconds: int = 10,
            ecgTypeString:        str = 'ECG-12',
            generatorModel:       str = 'Default',
            request:              gradio.Request = None) -> list:

   ecgLengthInSeconds = 10

   log(f'Session "{request.session_hash}": Generate EGCs!')


   # ====== Set ECG type ====================================================
   ecgType = deepfakeecg.DATA_ECG12
   if ecgTypeString == 'ECG-8':
      ecgType = deepfakeecg.DATA_ECG8
   elif ecgTypeString == 'ECG-12':
      ecgType = deepfakeecg.DATA_ECG12
   else:
      sys.stderr.write(f'WARNING: Invalid ecgTypeString {ecgTypeString}, using ECG-12!\n')

   # ====== Raise Locator.MAXTICKS, if necessary ============================
   matplotlib.ticker.Locator.MAXTICKS = \
       max(1000, ecgLengthInSeconds * deepfakeecg.ECG_SAMPLING_RATE)
   # print(matplotlib.ticker.Locator.MAXTICKS)

   # ====== Generate the ECGs ===============================================
   Sessions[request.session_hash].Results = \
      deepfakeecg.generateDeepfakeECGs(numberOfECGs,
                                       ecgType            = ecgType,
                                       ecgLengthInSeconds = ecgLengthInSeconds,
                                       ecgScaleFactor     = deepfakeecg.ECG_DEFAULT_SCALE_FACTOR,
                                       outputFormat       = deepfakeecg.OUTPUT_TENSOR,
                                       showProgress       = False,
                                       runOnDevice        = runOnDevice)
   Sessions[request.session_hash].Type = ecgType

   # ====== Create a list of image/label tuples for gradio.Gallery ==========
   plotList  = []
   ecgNumber = 1
   info      = '25 mm/sec, 1 mV/10 mm'
   for result in Sessions[request.session_hash].Results:

      # ====== Plot ECG =====================================================
      # 1. Convert to NumPy
      # 2. Remove the Timestamp column (0)
      # 3. Convert from µV to mV
      result = result.t().detach().cpu().numpy()[1:] / 1000
      # print(result)

      # ------ ECG-12 -------------------------------------------------------
      if ecgType == deepfakeecg.DATA_ECG12:
         ecg_plot.plot(result,
                       title       = 'ECG-12 – ' + info,
                       sample_rate = deepfakeecg.ECG_SAMPLING_RATE,
                       lead_index  = [ 'I', 'II', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6', 'III', 'aVR', 'aVL', 'aVF' ],
                       lead_order  = [0, 1, 8, 9, 10, 11, 2, 3, 4, 5, 6, 7],
                       show_grid   = True)
      # ------ ECG-8 --------------------------------------------------------
      else:
         ecg_plot.plot(result,
                       title       = 'ECG-8 – ' + info,
                       sample_rate = deepfakeecg.ECG_SAMPLING_RATE,
                       lead_index  = [ 'I', 'II', 'V1', 'V2', 'V3', 'V4', 'V5', 'V6' ],
                       lead_order  = [0, 1, 2, 3, 4, 5, 6, 7],
                       show_grid   = True)

      # ====== Generate WebP output =========================================
      imageBuffer = io.BytesIO()
      plt.savefig(imageBuffer, format = 'webp')
      plt.close()
      image = PIL.Image.open(imageBuffer)
      plotList.append( (image, f'ECG Number {ecgNumber}') )

      ecgNumber = ecgNumber + 1

   return plotList


# ###### Select ECG in the gallery ##########################################
def select(event:   gradio.SelectData,
           request: gradio.Request):
   # Get selection index from Gallery select() event:
   # https://github.com/gradio-app/gradio/issues/1976#issuecomment-1726018500

   Sessions[request.session_hash].Selected = event.index
   log(f'Session "{request.session_hash}": Selected ECG #{Sessions[request.session_hash].Selected + 1}')


# ###### Download CSV #######################################################
def downloadCSV(request: gradio.Request) -> pathlib.Path:

   ecgResult = Sessions[request.session_hash].Results[Sessions[request.session_hash].Selected]
   ecgType   = Sessions[request.session_hash].Type
   fileName  = pathlib.Path(Sessions[request.session_hash].TempDirectory.name) / \
                  ('ECG-' + str(Sessions[request.session_hash].Selected + 1) + '.csv')
   deepfakeecg.dataToCSV(ecgResult, ecgType, fileName)

   log(f'Session "{request.session_hash}": Download CSV file {fileName}')
   return fileName



# ###### Download PDF #######################################################
def downloadPDF(request: gradio.Request):

   ecgResult = Sessions[request.session_hash].Results[Sessions[request.session_hash].Selected]
   ecgType   = Sessions[request.session_hash].Type
   fileName  = pathlib.Path(Sessions[request.session_hash].TempDirectory.name) / \
                  ('ECG-' + str(Sessions[request.session_hash].Selected + 1) + '.pdf')
   if ecgType == deepfakeecg.DATA_ECG12:
      outputLeads = [ 'I', 'II', 'III', 'aVL', 'aVR', 'aVF', 'V1', 'V2', 'V3', 'V4' , 'V5' , 'V6' ]
   else:
      outputLeads = [ 'I', 'II', 'V1', 'V2', 'V3', 'V4' , 'V5' , 'V6' ]

   deepfakeecg.dataToPDF(ecgResult, ecgType, outputLeads, fileName,
                         Sessions[request.session_hash].Selected + 1)

   log(f'Session "{request.session_hash}": Download PDF file {fileName}')
   return fileName


# ###### Analyze the selected ECG ###########################################
def analyze(request: gradio.Request):

   log(f'Session "{request.session_hash}": Analyze ECG #{Sessions[request.session_hash].Selected + 1}!')

   data = Sessions[request.session_hash].Results[Sessions[request.session_hash].Selected]
   print(data)



# ###### Main program #######################################################

# ====== Initialise =========================================================
runOnDevice: typing.Literal['cpu', 'cuda'] = 'cuda' if torch.cuda.is_available() else 'cpu'
css = r"""
div {
   background-image: url("https://www.nntb.no/~dreibh/graphics/backgrounds/background-essen.png");
}

/* ###### General Settings ##############################################  */
html, body {
   height:           100%;
   padding:          0;
   margin:           0;
   font-family:      sans-serif;
   font-size:        small;
   background-color: #E3E3E3;   /* Simula background colour: #E3E3E3 */
}


/* ###### Header ########################################################  */
div.header {
   background-image: none;
   background-color: #F15D22;   /* Simula header colour: #F15D22 */
   height:           7.5%;
   display:          flex;
   justify-content:  space-between;
}

div.logo-left {
   width:            12.5%;
   float:            left;
   display:          flex;
   padding:          0% 1%;
   align-items:      center;
   background:       white;
}

div.logo-right {
   width:            12.5%;
   float:            right;
   display:          flex;
   padding:          0% 1%;
   align-items:      center;
   background:       white;
}

div.title {
   display:          flex;
   align-items:      center;
   padding:          0% 1%;
   background-image: none;
   background-color: #F15D22;   /* Simula header colour: #F15D22 */

   font-family:      "Ubuntu", sans-serif;
   font-size:        4vh;
   font-weight:      bold;
}r

img.logo-image {
   max-width:        100%;
   max-height:       100%;
}
"""


# ====== Create GUI =========================================================
with gradio.Blocks(css = css, theme = gradio.themes.Glass(secondary_hue=gradio.themes.colors.blue)) as gui:

   # ====== Session handling ================================================
   # Session initialization, to be called when page is loaded
   gui.load(initializeSession)
   # Session clean-up, to be called when page is closed/refreshed
   gui.unload(cleanUpSession)

   # ====== Header ==========================================================
   big_block = gradio.HTML("""
<div class="header">
   <div class="logo-left">
      <img class="logo-image" src="data:image/svg+xml;base64,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" alt="SimulaMet" height="32" />
   </div>
   <div class="title" id="title"><a href="https://ihi-search.eu/">SEARCH</a>&nbsp;Fake ECG Generator</div>
   <div class="logo-right">
      <img class="logo-image" src="data:image/svg+xml;base64,PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiPz4NCjwhLS0gR2VuZXJhdG9yOiBBZG9iZSBJbGx1c3RyYXRvciAxNS4wLjAsIFNWRyBFeHBvcnQgUGx1Zy1JbiAuIFNWRyBWZXJzaW9uOiA2LjAwIEJ1aWxkIDApICAtLT4NCjwhRE9DVFlQRSBzdmcgUFVCTElDICItLy9XM0MvL0RURCBTVkcgMS4xLy9FTiIgImh0dHA6Ly93d3cudzMub3JnL0dyYXBoaWNzL1NWRy8xLjEvRFREL3N2ZzExLmR0ZCI+DQo8c3ZnIHZlcnNpb249IjEuMSIgaWQ9IkxheWVyXzEiIHhtbG5zPSJodHRwOi8vd3d3LnczLm9yZy8yMDAwL3N2ZyIgeG1sbnM6eGxpbms9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkveGxpbmsiIHg9IjBweCIgeT0iMHB4Ig0KCSB3aWR0aD0iMTAzNy44OTVweCIgaGVpZ2h0PSIxNzQuMjVweCIgdmlld0JveD0iMCAwIDEwMzcuODk1IDE3NC4yNSIgZW5hYmxlLWJhY2tncm91bmQ9Im5ldyAwIDAgMTAzNy44OTUgMTc0LjI1Ig0KCSB4bWw6c3BhY2U9InByZXNlcnZlIj4NCjxnPg0KCTxwYXRoIGZpbGw9IiNGMTVBMjIiIGQ9Ik0xMTUuMTAzLDIwLjkzN2MwLDEwLjIyNiw4LjM0MywxOC44NCwxOC40ODEsMTguODRjMTAuMzcxLDAsMTguNDcyLTguNjE0LDE4LjQ3Mi0xOC44NA0KCQljMC0xMC42OTEtOC4xMDEtMTkuMjk2LTE4LjQ3Mi0xOS4yOTZDMTIzLjQ0NSwxLjY0MSwxMTUuMTAzLDEwLjI0NSwxMTUuMTAzLDIwLjkzNyBNNTEyLjI1NiwxNzAuMjIyaC0yNy4zMzdWNy4xOTloMjcuMzM3VjE3MC4yMjINCgkJeiBNMTQ3LjI1Miw1Ni4wNzVoLTI3LjM1OHYxMTQuMTI3aDI3LjM1OFY1Ni4wNzV6IE0zNjMuODY2LDU2LjA5NWgyNy4zMzh2NjAuNjcyYzAsOC4xMywwLjIzMywxNi4wNDYsMi44NzEsMjIuMDQyDQoJCWMyLjYzOSw1Ljk3Niw3LjkxNiwxMC4wNjgsMTcuNSwxMC4wNjhjMTcuMDE3LDAsMjQuNDQ4LTEzLjE5MiwyNC40NDgtMzEuNjQ1VjU2LjA5NWgyNy4zMzl2MTE0LjEyN2gtMjcuMzM5di0xNC42NDkNCgkJYy01LjUwOSw5LjYwNS0xNy43NTIsMTcuNTIxLTM0LjAzMiwxNy41MjFjLTExLjUwNiwwLTIxLjM0My0zLjYwOC0yOC4wNTctMTEuMDQxYy03LjE5Ny04LjE0Ny0xMC4wNjgtMTYuMDQ1LTEwLjA2OC00MS4yM1Y1Ni4wOTV6DQoJCSBNMjU5LjU0NSw2NC4yNDNjLTYuNzEzLTcuNDMxLTE2LjU1LTExLjAyMS0yOC4yODktMTEuMDIxYy0xNy45ODYsMC0zMC4xOTEsNy44OTYtMzUuNzIsMTcuNTAydi0xNC42M2gtMjcuMzE5djExNC4xMjdoMjcuMzE5DQoJCXYtNjEuMTM5YzAtMTguNDcyLDcuOTE2LTMxLjY0NiwyNC42OTktMzEuNjQ2YzIwLjYyNSwwLDIyLjA2MSwxNC4zNzcsMjIuMDYxLDM1LjAwMnY1Ny43ODJoMjcuMzM4di02MS4xMzkNCgkJYzAtMTguNDcyLDcuNjY1LTMxLjY0NiwyNC42ODEtMzEuNjQ2YzIwLjYwNSwwLDIyLjA2MSwxNC4zNzcsMjIuMDYxLDM1LjAwMnY1Ny43ODJoMjcuMzE5di02NC43MjkNCgkJYzAtMjUuMTY1LTIuODUzLTMzLjEwMS0xMC4wNTEtNDEuMjVjLTUuOTk2LTYuNzEzLTE1LjYtMTEuMDIxLTMwLjIyOS0xMS4wMjFjLTIwLjYwNiwwLTMyLjExMiw5LjM1Mi0zOS4wNzcsMTcuNzMzDQoJCUMyNjIuOTAyLDY4LjU1MiwyNjEuNDg1LDY2LjQxNiwyNTkuNTQ1LDY0LjI0MyBNODQuNDQ2LDg4LjQ1OEM3Ni41NCw4MC43OTQsNjUuNTEsNzUuNTE3LDUyLjMxNSw3NS41MTcNCgkJYy0xMC43ODgsMC0xOC42OTQsMy44MjItMTguNjk0LDExLjI1NGMwLDguMTY4LDcuOTA2LDkuODM3LDIzLjk4MSwxMy4xOTNsMTMuNjUsMy4xMjRjMTcuMjY5LDQuMDc0LDMyLjg2OCwxMC41NTUsMzIuODY4LDMxLjQxMg0KCQljMCwyNi4xMzYtMjMuNzQ5LDM4LjU5My00OS44NzQsMzguNTkzYy0yNy4zMzksMC00NS44LTEzLjQyNy01Mi43NDYtMjMuMjQ0bDE4LjQ1MS0xNi4zMTgNCgkJYzYuNDgxLDguNjM2LDE3LjUwMiwxNy4wMTcsMzUuMDEzLDE3LjAxN2MxMy42NjksMCwyMS41NzUtNC43NzMsMjEuNTc1LTEyLjkyNGMwLTcuOTM1LTYuNDgtOS4zNy0xNy41MDEtMTEuNzU3bC0xNy4wMzUtMy42MDgNCgkJQzIyLjExNiwxMTcuOTUsNi41NDQsMTA5LjU2OCw2LjU0NCw4OC43MWMwLTI0LjkzMywyNC4xOTUtMzUuNDg3LDQ2LjAxNC0zNS40ODdjMjIuNzg4LDAsNDAuMjcsMTAuMDY5LDQ3LjcyMSwxOC4yMkw4NC40NDYsODguNDU4DQoJCXogTTYyOC4wNywxNDQuMjZWODcuNjYyYzAtMjUuMTY1LTE5LjIwOS0zMy41NDctNDUuMzI0LTMzLjU0N2MtMjcuMzM5LDAtNTAuMzUsMTEuMjUzLTQ5Ljg2NSwzOS4zMTFsMjUuNjUsMS42NjgNCgkJYy0wLjI1My0xMy40MjcsNy42NjUtMTkuODg4LDIzLjAxMi0xOS44ODhjMTQuMTYzLDAsMjAuMzczLDQuNzkyLDIwLjM3MywxNC4zOTZ2MS45MDJjMCw0LjMwNy0xLjE4Myw0Ljc5Mi03LjE5OCw1Ljk5NA0KCQlsLTI1LjE2Niw0LjMyN2MtMTQuODYxLDIuNjQtMjYuODM0LDcuMTgtMzMuOCwxNS41NjJjLTQuMDczLDUuMDQ1LTYuNDc5LDExLjUyNC02LjQ3OSwyMC4xNTkNCgkJYzAsMjQuOTMzLDE4LjIxOSwzNS45NTMsNDAuMjc4LDM1Ljk1M2MxOS42NTUsMCwyNy4zOTYtOS43MDEsMzIuNDAzLTE0LjY0OHYxMS4xNzZoMjYuMDk4di0yNS42MzENCgkJQzYyOC4wNTMsMTQ0LjM1Nyw2MjguMDcsMTQ0LjMsNjI4LjA3LDE0NC4yNiBNNjAxLjkxNiwxMjkuODYzYzAsMTUuNTgtMTAuMjg0LDIzLjAxMi0yNS4xNjYsMjMuMDEyDQoJCWMtMTMuNDI3LDAtMTkuNjUzLTYuMjI5LTE5LjY1My0xNS41ODFjMC05LjExOCw1Ljc2Mi0xMi40NzYsMTguNzA0LTE1LjA5NWwxMC41MzMtMi4xNTRjOC4xNS0xLjY2OCwxMS41MDctMi42NTcsMTUuNTgyLTQuMDczDQoJCVYxMjkuODYzeiIvPg0KCTxwYXRoIGZpbGw9IiMyNDEzNjMiIGQ9Ik0xMDM2LjUyNSwxNDkuMzgxYy0yLjg4NCwwLjQ4LTcuMjA5LDAuOTYxLTEyLjAxNiwwLjk2MWMtNC44MDYsMC05LjM3MS0wLjcyMS0xMS41MzQtMy4xMjQNCgkJYy0yLjE2My0yLjE2Mi0zLjEyNC01LjI4Ni0zLjEyNC0xMS43NzRWNzcuMDUyaDI2LjY3NFY1NS42NjZoLTI2LjY3NFY5Ljc3bC0yNy4zOTMsNi4wMDd2MzkuODloLTI0LjUxdjIxLjM4NmgyNC41MXY2Mi45NTgNCgkJYzAsMTEuMDUzLDAuMjQsMTcuNTQxLDQuODA1LDIzLjA2N2M2LjI0OCw3LjY4OSwxNy43ODIsOS44NTMsMjguODM2LDkuODUzYzguMTcsMCwxNS4xMzktMC43MjEsMjAuNDI2LTEuOTIyVjE0OS4zODF6DQoJCSBNODk5LjMxNiw3NC44OWMxNS4zNzksMCwyNi4xOTEsMTAuMDkyLDI2LjkxMiwyNC45OWgtNTUuNzQ5Qzg3MS4yMDEsODYuMTgzLDg4My42OTcsNzQuODksODk5LjMxNiw3NC44OSBNOTM0Ljg3OSwxMjkuNjc3DQoJCWMtMy42MDQsNS43NjctMTIuNzM1LDE5LjcwNC0zMy40MDEsMTkuNzA0Yy0yMC4xODQsMC0yOS43OTYtMTMuNDU2LTMxLjcxOS0yOS4wNzZoODMuMzgzYzAtMS45MjIsMC4yNC01LjA0NiwwLjI0LTYuOTY4DQoJCWMwLTM1LjA4My0xNy41NDEtNjAuMzE0LTU0LjA2NS02MC4zMTRjLTMxLjk2MSwwLTU2LjIyOSwyMy41NDktNTYuMjI5LDU4Ljg3MmMwLDM3LjAwNSwyMy4wNjgsNjEuMDM1LDU2Ljk1LDYxLjAzNQ0KCQljMzMuNCwwLDQ4Ljc3OS0yMC45MDYsNTMuODI2LTI4LjgzNUw5MzQuODc5LDEyOS42Nzd6IE03NDAuOTYyLDYzLjgzNmMtNi43MjgtNy40NDktMTYuNTgtMTEuMDU1LTI4LjM1NS0xMS4wNTUNCgkJYy0xOC4wMjEsMC0zMC4yNzYsNy45MzEtMzUuODA0LDE3LjU0MlY1NS42NjZINjQ5LjQxdjExNC4zOGgyNy4zOTN2LTYxLjI3NWMwLTE4LjUwMyw3LjkzLTMxLjcxOSwyNC43NTEtMzEuNzE5DQoJCWMyMC42NjUsMCwyMi4xMDcsMTQuNDE4LDIyLjEwNywzNS4wODN2NTcuOTExaDI3LjM5M3YtNjEuMjc1YzAtMTguNTAzLDcuNjktMzEuNzE5LDI0Ljc1MS0zMS43MTkNCgkJYzIwLjY2NSwwLDIyLjEwNywxNC40MTgsMjIuMTA3LDM1LjA4M3Y1Ny45MTFoMjcuMzk0di02NC44NzljMC0yNS4yMzEtMi44ODQtMzMuMTYxLTEwLjA5My00MS4zMzENCgkJYy02LjAwNy02LjcyOS0xNS42MTktMTEuMDU1LTMwLjI3Ny0xMS4wNTVjLTIwLjY2NSwwLTMyLjE5OSw5LjM3Mi0zOS4xNjgsMTcuNzgyQzc0NC4zMjYsNjguMTYsNzQyLjg4NCw2NS45OTksNzQwLjk2Miw2My44MzYiLz4NCjwvZz4NCjwvc3ZnPg0K" alt="NorNet" height="64" />
   </div>
</div>
""")
   gradio.Markdown('## Settings')
   with gradio.Row():
      sliderNumberOfECGs     = gradio.Slider(1, 100, label="Number of ECGs", step = 1, value = 4, interactive = True)
      # sliderLengthInSeconds = gradio.Slider(5, 60, label="Length (s)", step = 5, value = 10, interactive = True)
      dropdownType           = gradio.Dropdown( [ 'ECG-12', 'ECG-8' ], label = 'ECG Type', interactive = True)
      dropdownGeneratorModel = gradio.Dropdown( [ 'Default' ], label = 'Generator Model', interactive = True)
      with gradio.Column():
         buttonGenerate = gradio.Button("Generate ECGs!")
         buttonAnalyze  = gradio.Button("Analyze this ECG!")
         with gradio.Row():
            buttonCSV = gradio.DownloadButton("Download CSV")
            buttonCSV_hidden = gradio.DownloadButton(visible=False, elem_id="download_csv_hidden")
            buttonPDF = gradio.DownloadButton("Download PDF")
            buttonPDF_hidden = gradio.DownloadButton(visible=False, elem_id="download_pdf_hidden")
   gradio.Markdown('## Output')
   with gradio.Row():
      outputGallery = gradio.Gallery(label      = 'output',
                                     columns    = [ 1 ],
                                     height     = 'auto',
                                     show_label = True,
                                     preview    = True)
      outputGallery.select(select)
   gradio.Markdown('## Analysis')

   # ====== Add click event handling for "Generate" button ==================
   buttonGenerate.click(predict,
                        inputs  = [ sliderNumberOfECGs,
                                    # sliderLengthInSeconds,
                                    dropdownType,
                                    dropdownGeneratorModel ],
                        outputs = [ outputGallery ]
                       )

   # ====== Add click event handling for "Analyze" button ===================
   buttonAnalyze.click(analyze)

   # ====== Add click event handling for download buttons ===================
   # Using hidden button and JavaScript, to generate download file on-the-fly:
   # https://github.com/gradio-app/gradio/issues/9230#issuecomment-2323771634
   buttonCSV.click(downloadCSV)
   buttonCSV.click(fn = downloadCSV, inputs = None, outputs = [ buttonCSV_hidden ]).then(
                      fn = None, inputs = None, outputs = None,
                      js = "() => document.querySelector('#download_csv_hidden').click()")
   buttonPDF.click(downloadPDF)
   buttonPDF.click(fn = downloadPDF, inputs = None, outputs = [ buttonPDF_hidden ]).then(
                      fn = None, inputs = None, outputs = None,
                      js = "() => document.querySelector('#download_pdf_hidden').click()")

   # ====== Run on startup ==================================================
   gui.load(predict,
            inputs  = [ sliderNumberOfECGs,
                        # sliderLengthInSeconds,
                        dropdownType,
                        dropdownGeneratorModel ],
            outputs = [ outputGallery ]
           )


# ====== Run the GUI ========================================================
if __name__ == "__main__":

   # ------ Prepare temporary directory -------------------------------------
   TempDirectory = tempfile.TemporaryDirectory(prefix = 'DeepFakeECGPlus-')
   log(f'Prepared temporary directory {TempDirectory.name}')

   # ------ Run the GUI, with downloads from temporary directory allowed ----
   gui.launch(allowed_paths = [ TempDirectory.name ])

   # ------ Clean up --------------------------------------------------------
   log(f'Cleaning up temporary directory {TempDirectory.name}')
   TempDirectory.cleanup()
   log('Done!')