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https://github.com/sbrl/research-rainfallradar
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dlr dsm: clash
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2 changed files with 3 additions and 3 deletions
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@ -58,7 +58,7 @@ dataset_train, dataset_validate = dataset_mono(
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output_size=IMAGE_SIZE,
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output_size=IMAGE_SIZE,
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input_size="same",
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input_size="same",
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filepath_heightmap=PATH_HEIGHTMAP,
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filepath_heightmap=PATH_HEIGHTMAP,
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remove_isolated_pixels=REMOVE_ISOLATED_PIXELS
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do_remove_isolated_pixels=REMOVE_ISOLATED_PIXELS
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)
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)
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logger.info("Train Dataset:", dataset_train)
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logger.info("Train Dataset:", dataset_train)
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@ -15,7 +15,7 @@ from .primitives.remove_isolated_pixels import remove_isolated_pixels
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# TO PARSE:
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# TO PARSE:
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def parse_item(metadata, output_size=100, input_size="same", water_threshold=0.1, water_bins=2, heightmap=None, rainfall_scale_up=1, remove_isolated_pixels=True):
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def parse_item(metadata, output_size=100, input_size="same", water_threshold=0.1, water_bins=2, heightmap=None, rainfall_scale_up=1, do_remove_isolated_pixels=True):
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if input_size == "same":
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if input_size == "same":
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input_size = output_size # This is almost always the case with e.g. the DeepLabV3+ model
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input_size = output_size # This is almost always the case with e.g. the DeepLabV3+ model
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@ -96,7 +96,7 @@ def parse_item(metadata, output_size=100, input_size="same", water_threshold=0.1
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# water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32)
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# water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32)
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# SPARSE [LOSS dice]
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# SPARSE [LOSS dice]
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water = tf.cast(tf.math.greater_equal(water, water_threshold), dtype=tf.float32)
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water = tf.cast(tf.math.greater_equal(water, water_threshold), dtype=tf.float32)
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if remove_isolated_pixels:
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if do_remove_isolated_pixels:
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water = remove_isolated_pixels(water)
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water = remove_isolated_pixels(water)
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print("DEBUG DATASET_OUT:rainfall shape", rainfall.shape)
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print("DEBUG DATASET_OUT:rainfall shape", rainfall.shape)
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