GASPExp002_SeqALSTM1x1Conv_6.json

{
    "checkpoint_model_dir": "gazenet/models/saliency_prediction/gasp/checkpoints/pretrained_sequencegaspencalstmconv",
    "experiment_name": "SequenceGASPEncALSTMConv",
    "inferer_name": "GASPInference",
    "log_dir": "logs",
    "logger": "comet",
    "model_name": "SequenceGASPEncALSTMConv",
    "model_properties": {
        "modalities": 5,
        "batch_size": 4,
        "sequence_len": 6,
        "sequence_norm": false
    },
    "project_name": "gasp_runs",
    "test_dataset_properties": {
        "csv_file": "datasets/processed/test_ave.csv",
        "video_dir": "datasets/processed/Grouped_frames",
        "inp_img_names_list": [
            "captured",
            "det_transformed_dave",
            "det_transformed_esr9",
            "det_transformed_vidgaze",
            "det_transformed_gaze360"
        ],
        "gt_img_names_list": [
            "transformed_salmap",
            "transformed_fixmap"
        ]
    },
    "train_dataset_properties": {
        "csv_file": "datasets/processed/train_ave.csv",
        "video_dir": "datasets/processed/Grouped_frames",
        "inp_img_names_list": [
            "captured",
            "det_transformed_dave",
            "det_transformed_esr9",
            "det_transformed_vidgaze",
            "det_transformed_gaze360"
        ],
        "gt_img_names_list": [
            "transformed_salmap",
            "transformed_fixmap"
        ]
    },
    "val_dataset_properties": {
        "csv_file": "datasets/processed/validation_ave.csv",
        "video_dir": "datasets/processed/Grouped_frames",
        "inp_img_names_list": [
            "captured",
            "det_transformed_dave",
            "det_transformed_esr9",
            "det_transformed_vidgaze",
            "det_transformed_gaze360"
        ],
        "gt_img_names_list": [
            "transformed_salmap",
            "transformed_fixmap"
        ]
    },
    "config_info": {
        "summary": "Sequential GASP: Sequential ALSTM variant. Exp_Variant_[N]{Norm} ->N: Context size; Norm: Enable temporal normalization;",
        "example": "python3 gazenet/bin/train.py --train_config GASPExp002_SeqALSTM1x1Conv_6 --gpus \"0\" --check_val_every_n_epoch 100 --max_epochs 10000 --checkpoint_save_every_n_epoch 100 --checkpoint_save_n_top 3"
    }
}