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mono: fix dataset preprocessing

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rogue dimension
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Starbeamrainbowlabs 2022-11-11 18:31:27 +00:00
parent 9035450213
commit 481eeb3759
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 2 additions and 2 deletions
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aimodel/src/lib/dataset/dataset_mono.py
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@ -34,10 +34,10 @@ def parse_item(metadata, shape_water_desired=[100,100], water_threshold=0.1, wat
rainfall = tf.transpose(rainfall, [1, 2, 0]) # channels_first → channels_last rainfall = tf.transpose(rainfall, [1, 2, 0]) # channels_first → channels_last
# rainfall = tf.image.resize(rainfall, tf.cast(tf.constant(metadata["rainfallradar"]) / 2, dtype=tf.int32)) # rainfall = tf.image.resize(rainfall, tf.cast(tf.constant(metadata["rainfallradar"]) / 2, dtype=tf.int32))
water = tf.expand_dims(water, axis=-1) # [width, height] → [width, height, channels] water = tf.expand_dims(water, axis=-1) # [width, height] → [width, height, channels=1]
water = tf.image.crop_to_bounding_box(water, water_offset_x, water_offset_y, water_width_target, water_height_target) water = tf.image.crop_to_bounding_box(water, water_offset_x, water_offset_y, water_width_target, water_height_target)
water = tf.squeeze(water)
water = tf.cast(tf.math.greater_equal(water, water_threshold), dtype=tf.int32) water = tf.cast(tf.math.greater_equal(water, water_threshold), dtype=tf.int32)
water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32) water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32)