Further improvements.

app.py

@@ -40,6 +40,8 @@ import gradio
 import io
 import matplotlib.pyplot as plt
 import matplotlib.ticker
+import numpy
+import pathlib
 import random
 import sys
 import tempfile
@@ -64,10 +66,24 @@ class Session:
 
    # ###### Constructor #####################################################
    def __init__(self):
-      self.Lock     = threading.Lock()
-      self.Counter  = 0
-      self.Results  = None
-      self.Selected = 0
+      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):
@@ -133,6 +149,7 @@ def predict(numberOfECGs:         int = 1,
                                        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  = []
@@ -182,10 +199,10 @@ def select(event:   gradio.SelectData,
    log(f'Session "{request.session_hash}": Selected ECG #{Sessions[request.session_hash].Selected + 1}')
 
 
-# ###### Produce CSV file from Tensor #######################################
-def dataToCSV(data, outputFileName, ecgType = deepfakeecg.DATA_ECG12) -> sys.path:
+# ###### Produce ECG CSV file from Tensor ###################################
+def dataToCSV(ecgResult, ecgType, outputFileName):
 
-   data = generatedECG.detach().cpu().numpy()
+   data = ecgResult.detach().cpu().numpy()
 
    if ecgType == deepfakeecg.DATA_ECG8:
       header = 'Timestamp,LeadI,LeadII,V1,V2,V3,V4,V5,V6'
@@ -195,20 +212,63 @@ def dataToCSV(data, outputFileName, ecgType = deepfakeecg.DATA_ECG12) -> sys.pat
       raise Exception('Invalid ECG type!')
 
    numpy.savetxt(outputFileName, data,
-                  header    = header,
-                  comments  = '',
-                  delimiter = ',',
-                  fmt       = '%i')
+                 header    = header,
+                 comments  = '',
+                 delimiter = ',',
+                 fmt       = '%i')
+
+
+# ###### Produce ECG PDF file from Tensor ###################################
+def dataToPDF(ecgResult, ecgType, outputFileName):
+
+   data = ecgResult.detach().cpu().numpy()
+   outputLeads = deepfakeecg.ECG_LEADS
+
+   matplotlib.pyplot.figure(figsize=(15, 3))
+   for outputLead in outputLeads:
+      try:
+         outputLeadIndex = deepfakeecg.ECG_LEADS[outputLead][0]
+         outputLeadLabel = deepfakeecg.ECG_LEADS[outputLead][1]
+         outputLeadType  = deepfakeecg.ECG_LEADS[outputLead][2]
+      except:
+         raise Exception('Invalid lead ' + outputLead + '!')
+      if outputLeadType > ecgType:
+         raise Exception('Invalid lead ' + outputLead + ' for this ECG type!')
+      matplotlib.pyplot.plot(data[:, outputLeadIndex], label = outputLeadLabel)
+   matplotlib.pyplot.legend()
+   matplotlib.pyplot.title('Generated ECG — ID ' + str(i))
+   matplotlib.pyplot.xlabel('Time [s]')
+   matplotlib.pyplot.ylabel('Amplitude [μV]')
+   matplotlib.pyplot.grid(True)
+   matplotlib.pyplot.ylim(-1000, +1000)
+   matplotlib.pyplot.savefig(outputFileName)
 
 
 # ###### Download CSV #######################################################
-def downloadCSV(request: gradio.Request):
-   log(f'Session "{request.session_hash}": Download CSV file')
+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')
+   dataToCSV(ecgResult, ecgType, fileName)
+
+   log(f'Session "{request.session_hash}": Download CSV file {fileName}')
+   return fileName
+
 
 
 # ###### Download PDF #######################################################
 def downloadPDF(request: gradio.Request):
-   log(f'Session "{request.session_hash}": Download PDF file')
+
+   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')
+   dataToPDF(ecgResult, ecgType, fileName)
+
+   log(f'Session "{request.session_hash}": Download PDF file {fileName}')
+   return fileName
 
 
 # ###### Analyze the selected ECG ###########################################
@@ -318,13 +378,17 @@ with gradio.Blocks(css = css, theme = gradio.themes.Glass(secondary_hue=gradio.t
          buttonGenerate = gradio.Button("Generate ECGs!")
          buttonAnalyze  = gradio.Button("Analyze this ECG!")
          with gradio.Row():
-            buttonCSV = gradio.Button("Download CSV")
-            buttonPDF = gradio.Button("Download PDF")
+            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',
+      outputGallery = gradio.Gallery(label      = 'output',
+                                     columns    = [ 1 ],
+                                     height     = 'auto',
                                      show_label = True,
-                                     preview = True)
+                                     preview    = True)
       outputGallery.select(select)
    gradio.Markdown('## Analysis')
 
@@ -341,8 +405,16 @@ with gradio.Blocks(css = css, theme = gradio.themes.Glass(secondary_hue=gradio.t
    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,
@@ -356,9 +428,14 @@ with gradio.Blocks(css = css, theme = gradio.themes.Glass(secondary_hue=gradio.t
 
 # ====== Run the GUI ========================================================
 if __name__ == "__main__":
-   TempDirectory = tempfile.TemporaryDirectory('DeepFakeECGPlus')
+   # ------ 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!')