From ce3d3a08094715aa6eee5cb528f4d78a9d40e44d Mon Sep 17 00:00:00 2001
From: Daniel Ecer <de-code@users.noreply.github.com>
Date: Fri, 28 Jul 2017 14:40:16 +0100
Subject: [PATCH] fixed: macro should have been micro
---
.../trainer/models/pix2pix/evaluate.py | 24 +++++++++----------
.../trainer/models/pix2pix/evaluate_test.py | 22 ++++++++---------
2 files changed, 23 insertions(+), 23 deletions(-)
diff --git a/sciencebeam_gym/trainer/models/pix2pix/evaluate.py b/sciencebeam_gym/trainer/models/pix2pix/evaluate.py
index 2cdb358..03d78b3 100644
--- a/sciencebeam_gym/trainer/models/pix2pix/evaluate.py
+++ b/sciencebeam_gym/trainer/models/pix2pix/evaluate.py
@@ -12,9 +12,9 @@ EvaluationTensors = collections.namedtuple(
"fp",
"fn",
"accuracy",
- "macro_precision",
- "macro_recall",
- "macro_f1"
+ "micro_precision",
+ "micro_recall",
+ "micro_f1"
]
)
@@ -33,18 +33,18 @@ def _evaluate_from_confusion_matrix(confusion, accuracy=None):
total_tp = tf.reduce_sum(tp)
total_fp = tf.reduce_sum(fp)
total_fn = tf.reduce_sum(fn)
- macro_precision = total_tp / (total_tp + total_fp)
- macro_recall = total_tp / (total_tp + total_fn)
- macro_f1 = 2 * macro_precision * macro_recall / (macro_precision + macro_recall)
+ micro_precision = total_tp / (total_tp + total_fp)
+ micro_recall = total_tp / (total_tp + total_fn)
+ micro_f1 = 2 * micro_precision * micro_recall / (micro_precision + micro_recall)
return EvaluationTensors(
confusion_matrix=confusion,
tp=tp,
fp=fp,
fn=fn,
accuracy=accuracy,
- macro_precision=macro_precision,
- macro_recall=macro_recall,
- macro_f1=macro_f1
+ micro_precision=micro_precision,
+ micro_recall=micro_recall,
+ micro_f1=micro_f1
)
def evaluate_predictions(labels, predictions, n_classes, has_unknown_class=False):
@@ -80,7 +80,7 @@ def evaluate_separate_channels(targets, outputs, has_unknown_class=False):
def evaluation_summary(evaluation_tensors):
- tf.summary.scalar("macro_precision", evaluation_tensors.macro_precision)
- tf.summary.scalar("macro_recall", evaluation_tensors.macro_recall)
- tf.summary.scalar("macro_f1", evaluation_tensors.macro_f1)
+ tf.summary.scalar("micro_precision", evaluation_tensors.micro_precision)
+ tf.summary.scalar("micro_recall", evaluation_tensors.micro_recall)
+ tf.summary.scalar("micro_f1", evaluation_tensors.micro_f1)
tf.summary.scalar("accuracy", evaluation_tensors.accuracy)
diff --git a/sciencebeam_gym/trainer/models/pix2pix/evaluate_test.py b/sciencebeam_gym/trainer/models/pix2pix/evaluate_test.py
index 976b977..5330211 100644
--- a/sciencebeam_gym/trainer/models/pix2pix/evaluate_test.py
+++ b/sciencebeam_gym/trainer/models/pix2pix/evaluate_test.py
@@ -31,21 +31,21 @@ def test_evaluate_predictions():
assert np.array_equal(session.run(evaluation_tensors.tp), np.array([1, 1, 0, 2]))
assert np.array_equal(session.run(evaluation_tensors.fp), np.array([0, 1, 1, 0]))
assert np.array_equal(session.run(evaluation_tensors.fn), np.array([0, 0, 1, 1]))
- expected_macro_precision = 4.0 / (4 + 2)
- expected_macro_recall = 4.0 / (4 + 2)
- expected_macro_f1 = (
- 2 * expected_macro_precision * expected_macro_recall /
- (expected_macro_precision + expected_macro_recall)
+ expected_micro_precision = 4.0 / (4 + 2)
+ expected_micro_recall = 4.0 / (4 + 2)
+ expected_micro_f1 = (
+ 2 * expected_micro_precision * expected_micro_recall /
+ (expected_micro_precision + expected_micro_recall)
)
assert _scalar_close(
- session.run(evaluation_tensors.macro_precision),
- expected_macro_precision
+ session.run(evaluation_tensors.micro_precision),
+ expected_micro_precision
)
assert _scalar_close(
- session.run(evaluation_tensors.macro_recall),
- expected_macro_recall
+ session.run(evaluation_tensors.micro_recall),
+ expected_micro_recall
)
assert _scalar_close(
- session.run(evaluation_tensors.macro_f1),
- expected_macro_f1
+ session.run(evaluation_tensors.micro_f1),
+ expected_micro_f1
)
--
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