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")