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dlr CHANGE: properly normalise the heightmap

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Starbeamrainbowlabs 2023-03-10 19:13:32 +00:00
parent 8e76ac2864
commit f25d1b5b1a
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 5 additions and 4 deletions
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9
aimodel/src/lib/dataset/dataset_mono.py
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@ -40,10 +40,11 @@ def parse_item(metadata, output_size=100, input_size="same", water_threshold=0.1
if heightmap is not None: if heightmap is not None:
heightmap = tf.expand_dims(heightmap, axis=-1) heightmap = tf.expand_dims(heightmap, axis=-1)
# NORMALLY, this wouldn't work 'cause you'd need to know the max of ALL frames, but here we only have a single frame. norm = tf.keras.layers.Normalization(axis=None)
heightmap_max = tf.math.reduce_max(heightmap) norm.adapt(heightmap)
heightmap_min = tf.math.reduce_min(tf.where(tf.math.less(heightmap, -500), heightmap, tf.fill(heightmap.shape, 0.0))) # THIS IS (probably) OK, because BatchNorm also outputs mean=0 stddev=1, bias term shifts anyway
heightmap = (heightmap - heightmap_min) / heightmap_max # Ref https://datascience.stackexchange.com/a/54383/86851
heightmap = norm(heightmap)
heightmap = tf.transpose(heightmap, [1, 0, 2]) # [width, height] → [height, width] heightmap = tf.transpose(heightmap, [1, 0, 2]) # [width, height] → [height, width]
def parse_item_inner(item): def parse_item_inner(item):