def OpenLabelImg(self):
"""
Opens labelimg.
"""
# Define current datasets directory to annotate
dataSet = self.autoAnnotateDialogue.dataSetsComboBox.currentText()
imgDir = os.path.join(config.datasets, dataSet)
modelName = ""
modelDir = ""
errorMsg = None
# Set variables
try:
if self.multiClassCheckBox:
modelName = self.autoAnnotateDialogue.annotatorComboBox.currentText(
)
modelDir = config.snapshots
else:
modelName = config.classesCSV
modelDir = ""
except Exception as e:
print("Could not get classes path. Reason: " + str(e)) #DEBUG
# Set classes file path
mapPath, mapFileFound = general_error.GetMapPath(modelName, modelDir)
if mapFileFound:
errorMsg = general.OpenLabelImg(imgDir, mapPath)
if errorMsg is not None:
errorMessage = "Could not open labelImg. Reason: " + errorMsg
self.autoAnnotateDialogue.textEdit.append(errorMessage)
def RunAnnotationButton(self):
"""
Runs when the RunAnnotationButton is clicked.
"""
# Set generate XML variable
self.generateXML = True
# If the multiclass option is set
if self.multiClassCheckBox:
# Set model directory
self.modelDir = config.snapshots
# Get currently selected model name
self.selectedModel = self.autoAnnotateDialogue.annotatorComboBox.currentText(
)
# Set map path
mapPath, mapFileFound = general_error.GetMapPath(config.classesCSV, "")
if mapFileFound:
self.mapPath = mapPath
# Set model directory
self.modelDir = config.snapshots
else:
# Set model directory
self.modelDir = config.pretrainedModels
# Set single class annotator model as default model
self.selectedModel = "single_class_annotator.h5"
# Set map path
mapPath, mapFileFound = general_error.GetMapPath(
self.selectedModel, self.modelDir)
if mapFileFound:
self.mapPath = mapPath
# Create classes CSV file
error, errorMsg = general.CreateClassString(self.selectedModel,
config.pretrainedModels,
self.annotateClassesSet)
if error:
errorMessage = "There was an error with creating CSV file: " + errorMsg
self.autoAnnotateDialogue.textEdit.append(errorMessage)
# Set self.cancelPreview value
self.cancelPreview = False
# Set first preview image variable for messaging
self.firstPreviewImage = True
# Chosen dataset
dataSet = self.autoAnnotateDialogue.dataSetsComboBox.currentText()
self.testImagesPath = os.path.join(config.datasets, dataSet)
# Set image count
enoughImages, imageCount, errorMessage = general_image.EnoughImages(
self.testImagesPath, 0)
if errorMessage is not None:
self.autoAnnotateDialogue.textEdit.append(errorMessage)
self.previewImagesNum = imageCount
# Set progress bar max value
self.inferenceProgressBarMaxValue = self.previewImagesNum
# Reset progress bar
self.autoAnnotateDialogue.progressBar.setValue(0)
# Set progress bar
ui_general.SetProgressBar(self, self.autoAnnotateDialogue)
# Start preview images thread
ui_general.StartPreviewThread(self, self.autoAnnotateDialogue)
# Disable widgets while processing images
StartToggleAaWidgets(self)
testImage = "test/test_images/1.jpg"
testModelName = "test_model"
testModelDir = "test"
testClassFile = "test_model.csv"
testString = "Test string."
print("Testing general_error.py\n")
# Test general_error.FileExists
fileExists, errorMsg = general_error.FileExists(testImage)
assert fileExists
assert errorMsg is None
print("general_error.FileExists passed")
# Test general_error.GetMapPath
mapPath, mapFilePath = general_error.GetMapPath(testModelName, testModelDir)
assert mapPath == os.path.join(testModelDir, testClassFile)
assert mapFilePath
print("general_error.GetMapPath passed")
# Test general_error.StringNotEmpty
notEmpty = general_error.StringNotEmpty(testString)
assert True
print("general_error.StringNotEmpty passed")
# Test general_error.CheckCSV
csvExist, error, errorMsg = general_error.CheckCSV()
assert csvExist
assert error is False
assert errorMsg is None
print("general_error.CheckCSV passed")
def RunInferenceButton(self):
"""
Run inference on selected model.
"""
# Set self.cancelPreview value
self.cancelPreview = False
# Set first preview image variable for messaging
self.firstPreviewImage = True
# Set model name
ui_general.SetModel(self, self.runInferenceDialogue)
# Ensure name is not empty
modelNotEmpty = general_error.StringNotEmpty(self.selectedModel)
# Ensure test images dir has been selected
imagesDirNotEmpty = general_error.StringNotEmpty(self.testImagesPath)
# Ensure image count is less than image dir image count.
enoughImages, imageCount, errorMessage = general_image.EnoughImages(
self.testImagesPath, self.previewImagesNum)
if errorMessage is not None:
self.runInferenceDialogue.textEdit.append(errorMessage)
if enoughImages is False:
self.previewImagesNum = imageCount
# Update preview images number
ui_general.SetPreviewImagesNum(self, self.runInferenceDialogue)
# Set progress bar max value
self.inferenceProgressBarMaxValue = self.previewImagesNum
# Set model directory
self.modelDir = config.pretrainedModels
# Set map name
mapPath, mapFileFound = general_error.GetMapPath(self.selectedModel,
config.pretrainedModels)
if mapFileFound:
self.mapPath = mapPath
# Reset progress bar
self.runInferenceDialogue.progressBar.setValue(0)
# Set progress bar
ui_general.SetProgressBar(self, self.runInferenceDialogue)
# Create thread to process images
if modelNotEmpty and imagesDirNotEmpty and mapFileFound:
ui_general.StartPreviewThread(self, self.runInferenceDialogue)
# Disable widgets while processing images
StartToggleRiWidgets(self)
# Update dialogue
self.runInferenceDialogue.textEdit.append("Commencing inference.")
else:
if modelNotEmpty is False:
QtWidgets.QMessageBox.information(self.runInferenceDialogue,
"No model found",
"Please select a model first.",
QtWidgets.QMessageBox.Ok)
if imagesDirNotEmpty is False:
QtWidgets.QMessageBox.information(
self.runInferenceDialogue, "No image directory selected",
"Please select a test images directory first.",
QtWidgets.QMessageBox.Ok)
if mapFileFound is False:
QtWidgets.QMessageBox.information(
self.runInferenceDialogue, "No map file found",
"The model you have selected does not have a map file. Please select a different model.",
QtWidgets.QMessageBox.Ok)