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xuebinqin / Binary-Segmentation-Evaluation-Tool

This repo is developed for evaluating binary image segmentation results. Measures, such as MAE, Precision, Recall, F-measure, PR curves and F-measure curves are included.
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PR-curve with the complete negative test sample #1

Closed songkq closed 4 years ago

songkq commented 4 years ago

Greeting! If there are some test samples without a salient object in the image, does it need to contain these samples when computing the PR-curve? Since the precision and recall keep zero with any threshold.

xuebinqin commented 4 years ago

Although the precision and recall on these images without foregrounds are ill defined, we didn’t explicitly exclude them when computing the measures. Their measures should be zeros due to the 1e-8 used in the denominator or precision and recall computation.

On Jul 26, 2020, at 12:19 AM, ipScore notifications@github.com wrote:

Greeting! If there are some test samples without a salient object in the image, does it need to contain these samples when computing the PR-curve? Since the precision and recall keep zero with any threshold.

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songkq commented 4 years ago

@NathanUA Thanks for your reply. I wonder it is reasonable to compute the average PR from the sum of each image? Why not to directly compute the PR from the whole dataset?