def ProDeeplearningMain(folder_test = '', folder_train = '', analysis_type = dict()):
if analysis_type["analysis_type"] == 0:
SegmentMain.segmentMain(folder_test, folder_train, analysis_type)
elif analysis_type["analysis_type"] == 1:
DetectionMain.detectionMain(folder_test, folder_train, analysis_type)
elif analysis_type["analysis_type"] == 2:
# detection + classify
# DetectionMain.detectionMain(folder_test, folder_train, analysis_type)
ClassifyMain.classifyMain(folder_test, folder_train, analysis_type)
else:
raise ValueError("Analysis Mapping Wrong")
print("Test folder: ", folder_test)
print("Analysis type: ", analysis_type)
print("complete")
def ProDeeplearningMain(folder_test='', folder_train='', analysis_type=dict()):
# convert 1024*1024 or 512*512 to 256*256
folder_test = cropImg(analysis_type, folder_test)
if analysis_type["analysis_type"] == 0:
SegmentMain.segmentMain(folder_test, folder_train, analysis_type)
elif analysis_type["analysis_type"] == 1:
DetectionMain.detectionMain(folder_test, folder_train, analysis_type)
elif analysis_type["analysis_type"] == 2:
# detection + classify
DetectionMain.detectionMain(folder_test, folder_train, analysis_type)
ClassifyMain.classifyMain(folder_test, folder_train, analysis_type)
else:
raise ValueError("Analysis Mapping Wrong")
print("Test folder: ", folder_test)
print("Analysis type: ", analysis_type)
print("complete")
