Fix demo_inference to properly normalize input #2978
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added 2 commits
December 7, 2017 11:04
Before the fix the demo_inference.py used batch_norm and it did the normalization of input image implicitly. If at inference time the batch_norm was disabled the inference produced incorrect results. This fix does the proper input image normalization and disables the batch_norm at inference time.
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@sguada Can you please review the change? |
sguada
approved these changes
Dec 13, 2017
| feed_dict={images_placeholder: images_data}) | ||
| print("Predicted strings:") | ||
| for line in predictions: | ||
| for line in run(FLAGS.checkpoint, FLAGS.batch_size, FLAGS.dataset_name, |
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Change to:
predictions = run(FLAGS.checkpoint, FLAGS.batch_size, FLAGS.dataset_name, FLAGS.image_path_pattern)
for line in predictions:
print(line)
sguada
requested changes
Dec 13, 2017
| feed_dict={images_placeholder: images_data}) | ||
| print("Predicted strings:") | ||
| for line in predictions: | ||
| for line in run(FLAGS.checkpoint, FLAGS.batch_size, FLAGS.dataset_name, |
added 3 commits
December 13, 2017 19:07
Use temp variable for predictions.
alexgorban
requested review from
MarkDaoust,
derekjchow,
ebrevdo,
jch1,
k-w-w,
lukaszkaiser and
nealwu
as code owners
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This PR was messed up with unsuccessful merges with the upstream. I will create a new one with the required changes to the Attention OCR only. |
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Before the fix the demo_inference.py used batch_norm and it did the normalization of input image implicitly. If at the inference time the batch_norm was disabled the inference produced incorrect results.
This fix: