6ee3771518f4567a9307d64ac38fa76909d7a414,niftynet/application/classification_application.py,ClassificationApplication,initialise_dataset_loader,#ClassificationApplication#Any#Any#Any#,67

Before Change

        // read each line of csv files into an instance of Subject
        if self.is_training:
            file_lists = []
            if self.action_param.validation_every_n > 0:
                file_lists.append(data_partitioner.train_files)
                file_lists.append(data_partitioner.validation_files)
            else:
                file_lists.append(data_partitioner.train_files)

            self.readers = []
            for file_list in file_lists:
                reader = ImageReader(["image", "label", "sampler"])
                reader.initialise(data_param, task_param, file_list)
                self.readers.append(reader)

        elif self.is_inference:  
            // in the inference process use image input only
            inference_reader = ImageReader(["image"])
            file_list = data_partitioner.inference_files
            inference_reader.initialise(data_param, task_param, file_list)
            self.readers = [inference_reader]
        elif self.is_evaluation:
            file_list = data_partitioner.inference_files
            reader = ImageReader({"image", "label", "inferred"})
            reader.initialise(data_param, task_param, file_list)
            self.readers = [reader]
        else:

After Change

        self.data_param = data_param
        self.classification_param = task_param

        file_lists = self.get_file_lists(data_partitioner)
        // read each line of csv files into an instance of Subject
        if self.is_training:
            self.readers = []
            for file_list in file_lists:
                reader = ImageReader(["image", "label", "sampler"])
                reader.initialise(data_param, task_param, file_list)
                self.readers.append(reader)

        elif self.is_inference:  
            // in the inference process use image input only
            inference_reader = ImageReader(["image"])
            inference_reader.initialise(data_param, task_param, file_lists[0])
            self.readers = [inference_reader]
        elif self.is_evaluation:
            reader = ImageReader({"image", "label", "inferred"})

Instances