config_test.yaml

random_state: 2022
log_output: false
out_dir: "./results_test"  # Required
data_in:
    csv: './data/dataset.csv'  # Required
    pkl: './data/data_MC_SZ_dict_256x256.pkl'  # Required - PKL with images redimensioned to 256x256
    models_ckpts_dir: './results'  # Required
img_dim_ai: 256
clahe:
    enabled: true
experimentDescription:
    experiment_name: "exp_ISBI_2023"  # Required - Please, write here the name of the folder which contains the different folds and model weights trained (typically, "exp_DDMMYYYY_HHMMSS").
experimentEnv:
    models: ['LightTBNet_4blocks']  # Please, check that the model selected matches with the weights located inside the model checkpoint folder. See config_train.yaml for further information about the models implemented.
    optimizers: ['Adam']  # Please, check that the optimizer selected matches with the weights located inside the model checkpoint folder
    losses: ['FocalLoss']
    ckpt_filename: "model_best.pth"  # "model_last.pth" to select the last model, not the best. Else, leave by default "model_best.pth"
    num_classes: 2
    training-dev_split: false
    test_batch_size: 16
    optim_args:
        Adam:
            learning_rate: 0.0001
            beta_1: 0.9
            beta_2: 0.999
            weight_decay: 0.0001
        SGD:
            learning_rate: 0.01
            weight_decay: 0.0001
        RMSprop:
            learning_rate: 0.01
            weight_decay: 0.0001
    apply_softmax: true
    pred_thresh: 0.5
    classes: ('no-TB', 'TB')
    cross_validation: 
        enabled: true
        k: 5