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fix water depth fiddling

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Starbeamrainbowlabs 2023-01-05 19:01:20 +00:00
parent 46d1f5e4e0
commit fefeb5d531
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 7 additions and 2 deletions
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9
aimodel/src/lib/dataset/dataset_segmenter.py
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@ -30,11 +30,16 @@ def parse_item(metadata, shape_water_desired, water_threshold=0.1, water_bins=2)
# SHAPES: # SHAPES:
# rainfall = [ feature_dim ] # rainfall = [ feature_dim ]
# water = [ width, height, 1 ] # water = [ height, width, 1 ] # yes, this is correct
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.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,
offset_height=water_offset_y,
offset_width =water_offset_x,
target_height=water_height_target,
target_width =water_width_target,
)
water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32) water = tf.one_hot(water, water_bins, axis=-1, dtype=tf.int32)
water = tf.reshape(water, tf.constant([water_width_target, water_height_target, water_bins], dtype=tf.int32)) water = tf.reshape(water, tf.constant([water_width_target, water_height_target, water_bins], dtype=tf.int32))
print("DEBUG:dataset ITEM rainfall:shape", rainfall.shape, "water:shape", water.shape) print("DEBUG:dataset ITEM rainfall:shape", rainfall.shape, "water:shape", water.shape)