Thesis-SampleAnalysis/run_keras.sh

# erase "models_info/models_comparisons.csv" file and write new header
file_path='models_info/models_comparisons_keras.csv'

erased=$1

if [ "${erased}" == "Y" ]; then
    echo "Previous data file erased..."
    rm ${file_path}
    mkdir -p models_info
    touch ${file_path}

    # add of header
    echo 'model_name; number_of_approximations; coeff_of_determination; MSE 10 samples; MSE 1000 samples;' >> ${file_path}
fi

for n in {3,4,5,6,7,8,9,10,15,20,25,30}; do
   for row in {1,2,3,4,5}; do
       for column in {1,2,3,4,5}; do

            # Run creation of dataset and train model
            DATASET_NAME="data/dataset_${n}_column_${column}_row_${row}.csv"
            MODEL_NAME="${n}_column_${column}_row_${row}_KERAS"
            IMAGE_RECONSTRUCTED="Sponza1_${n}_${row}_${column}.png"

            if ! grep -q "${MODEL_NAME}" "${file_path}"; then
                echo "Run computation for model ${MODEL_NAME}"

                # Already computed..
                #python make_dataset.py --n ${n} --each_row ${row} --each_column ${column}
                python train_model_keras.py --data ${DATASET_NAME} --model_name ${MODEL_NAME}

                # TODO : Add of reconstruct process for image ?
                python reconstruct_keras.py --n ${n} --model_path saved_models/${MODEL_NAME}.json --scene Sponza1 --image_name ${IMAGE_RECONSTRUCTED}
                python write_result_keras.py --n ${n} --model_path saved_models/${MODEL_NAME}.json --scene Sponza1 --image_path reconstructed/${IMAGE_RECONSTRUCTED} --data ${DATASET_NAME} --iqa mse &
            else
                echo "${MODEL_NAME} results already computed.."
            fi
        done
    done
done