From 623208ba6d746cf6713954ec85e6d6d00060568f Mon Sep 17 00:00:00 2001 From: Starbeamrainbowlabs Date: Tue, 14 Mar 2023 20:18:39 +0000 Subject: [PATCH] dlr: add env var for water thresholding --- aimodel/slurm-TEST-deeplabv3p-rainfall.job | 3 ++- aimodel/src/deeplabv3_plus_test_rainfall.py | 3 ++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/aimodel/slurm-TEST-deeplabv3p-rainfall.job b/aimodel/slurm-TEST-deeplabv3p-rainfall.job index 31bad59..bcdae73 100755 --- a/aimodel/slurm-TEST-deeplabv3p-rainfall.job +++ b/aimodel/slurm-TEST-deeplabv3p-rainfall.job @@ -38,6 +38,7 @@ show_help() { echo -e " EPOCHS The number of epochs to train for." >&2; echo -e " LOSS The loss function to use. Default: cross-entropy (possible values: cross-entropy, cross-entropy-dice)." >&2; echo -e " DICE_LOG_COSH When in cross-entropy-dice mode, in addition do loss = cel + log(cosh(dice_loss)) instead of just loss = cel + dice_loss." >&2; + echo -e " WATER_THRESHOLD The threshold to cut water off at when training, in metres. Default: 0.1" >&2; echo -e " PATH_CHECKPOINT The path to a checkcpoint to load. If specified, a model will be loaded instead of being trained." >&2; echo -e " LEARNING_RATE The learning rate to use. Default: 0.001." >&2; echo -e " PREDICT_COUNT The number of items from the (SCRAMBLED) dataset to make a prediction for." >&2; @@ -70,7 +71,7 @@ echo -e ">>> DIR_OUTPUT: ${DIR_OUTPUT}"; echo -e ">>> Additional args: ${ARGS}"; export PATH=$HOME/software/bin:$PATH; -export IMAGE_SIZE BATCH_SIZE DIR_RAINFALLWATER PATH_HEIGHTMAP PATH_COLOURMAP STEPS_PER_EPOCH DIR_OUTPUT PATH_CHECKPOINT EPOCHS PREDICT_COUNT NO_REMOVE_ISOLATED_PIXELS LOSS LEARNING_RATE DICE_LOG_COSH; +export IMAGE_SIZE BATCH_SIZE DIR_RAINFALLWATER PATH_HEIGHTMAP PATH_COLOURMAP STEPS_PER_EPOCH DIR_OUTPUT PATH_CHECKPOINT EPOCHS PREDICT_COUNT NO_REMOVE_ISOLATED_PIXELS LOSS LEARNING_RATE DICE_LOG_COSH WATER_THRESHOLD; echo ">>> Installing requirements"; conda run -n py38 pip install -q -r requirements.txt; diff --git a/aimodel/src/deeplabv3_plus_test_rainfall.py b/aimodel/src/deeplabv3_plus_test_rainfall.py index 9ca7b6d..3713410 100755 --- a/aimodel/src/deeplabv3_plus_test_rainfall.py +++ b/aimodel/src/deeplabv3_plus_test_rainfall.py @@ -49,6 +49,7 @@ EPOCHS = int(os.environ["EPOCHS"]) if "EPOCHS" in os.environ else 50 LOSS = os.environ["LOSS"] if "LOSS" in os.environ else "cross-entropy-dice" DICE_LOG_COSH = True if "DICE_LOG_COSH" in os.environ else False LEARNING_RATE = float(os.environ["LEARNING_RATE"]) if "LEARNING_RATE" in os.environ else 0.001 +WATER_THRESHOLD = float(os.environ["WATER_THRESHOLD"]) if "WATER_THRESHOLD" in os.environ else 0.1 DIR_OUTPUT=os.environ["DIR_OUTPUT"] if "DIR_OUTPUT" in os.environ else f"output/{datetime.utcnow().date().isoformat()}_deeplabv3plus_rainfall_TEST" @@ -76,7 +77,7 @@ for env_name in [ "BATCH_SIZE","NUM_CLASSES", "DIR_RAINFALLWATER", "PATH_HEIGHTM dataset_train, dataset_validate = dataset_mono( dirpath_input=DIR_RAINFALLWATER, batch_size=BATCH_SIZE, - water_threshold=0.1, + water_threshold=WATER_THRESHOLD, rainfall_scale_up=2, # done BEFORE cropping to the below size output_size=IMAGE_SIZE, input_size="same",