Fix tick labels for background FN/FP (#9414)
* Fix tick labels for background FN/FP In the confusion matrix. * Remove FP/FN from the background labels of the confusion matrix * Update metrics.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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@@ -170,12 +170,12 @@ class ConfusionMatrix:
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if n and sum(j) == 1:
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if n and sum(j) == 1:
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self.matrix[detection_classes[m1[j]], gc] += 1 # correct
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self.matrix[detection_classes[m1[j]], gc] += 1 # correct
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else:
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else:
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self.matrix[self.nc, gc] += 1 # background FP
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self.matrix[self.nc, gc] += 1 # true background
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if n:
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if n:
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for i, dc in enumerate(detection_classes):
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for i, dc in enumerate(detection_classes):
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if not any(m1 == i):
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if not any(m1 == i):
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self.matrix[dc, self.nc] += 1 # background FN
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self.matrix[dc, self.nc] += 1 # predicted background
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def matrix(self):
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def matrix(self):
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return self.matrix
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return self.matrix
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@@ -197,6 +197,7 @@ class ConfusionMatrix:
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nc, nn = self.nc, len(names) # number of classes, names
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nc, nn = self.nc, len(names) # number of classes, names
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sn.set(font_scale=1.0 if nc < 50 else 0.8) # for label size
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sn.set(font_scale=1.0 if nc < 50 else 0.8) # for label size
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labels = (0 < nn < 99) and (nn == nc) # apply names to ticklabels
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labels = (0 < nn < 99) and (nn == nc) # apply names to ticklabels
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ticklabels = (names + ['background']) if labels else "auto"
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with warnings.catch_warnings():
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with warnings.catch_warnings():
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warnings.simplefilter('ignore') # suppress empty matrix RuntimeWarning: All-NaN slice encountered
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warnings.simplefilter('ignore') # suppress empty matrix RuntimeWarning: All-NaN slice encountered
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sn.heatmap(array,
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sn.heatmap(array,
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@@ -208,8 +209,8 @@ class ConfusionMatrix:
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fmt='.2f',
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fmt='.2f',
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square=True,
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square=True,
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vmin=0.0,
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vmin=0.0,
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xticklabels=names + ['background FP'] if labels else "auto",
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xticklabels=ticklabels,
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yticklabels=names + ['background FN'] if labels else "auto").set_facecolor((1, 1, 1))
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yticklabels=ticklabels).set_facecolor((1, 1, 1))
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ax.set_ylabel('True')
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ax.set_ylabel('True')
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ax.set_ylabel('Predicted')
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ax.set_ylabel('Predicted')
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ax.set_title('Confusion Matrix')
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ax.set_title('Confusion Matrix')
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