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batch data; use generator
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1 changed files with 21 additions and 18 deletions
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@ -7,6 +7,7 @@ import re
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from loguru import logger
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from loguru import logger
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import tensorflow as tf
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import tensorflow as tf
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from lib.dataset.batched_iterator import batched_iterator
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from lib.vis.segmentation_plot import segmentation_plot
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from lib.vis.segmentation_plot import segmentation_plot
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from lib.io.handle_open import handle_open
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from lib.io.handle_open import handle_open
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@ -87,10 +88,12 @@ def run(args):
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sys.stderr.write(">>> Complete\n")
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sys.stderr.write(">>> Complete\n")
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def do_png(args, ai, dataset, model_code):
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def do_png(args, ai, dataset, model_code):
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i = 0
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model_params = json.loads(readfile(args.params))
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for rainfall, water in dataset:
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water_predict = ai.embed(rainfall)
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i = 0
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for rainfall, water in batched_iterator(dataset, tensors_in_item=2, batch_size=model_params["batch_size"]):
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water_predict_batch = ai.embed(rainfall)
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for water_predict in water_predict_batch:
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# [ width, height, softmax_probabilities ] → [ batch, width, height ]
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# [ width, height, softmax_probabilities ] → [ batch, width, height ]
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water_predict = tf.math.argmax(water_predict, axis=-1)
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water_predict = tf.math.argmax(water_predict, axis=-1)
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# [ width, height ]
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# [ width, height ]
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