Update the readme files.

lartpang · Dec 16, 2023 · c413a23 · c413a23
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diff --git a/py_sod_metrics/multiscale_iou.py b/py_sod_metrics/multiscale_iou.py
@@ -7,16 +7,15 @@
 class MSIoU:
     def __init__(self):
         """
-        Multiscale Intersection over Union (MS-IoU) metric.
+        Multi-Scale Intersection over Union (MSIoU) metric.
 
         ::
 
-            @inproceedings{ahmadzadehMultiscaleIOUMetric2021,
+            @inproceedings{MSIoU,
                 title = {Multiscale IOU: A Metric for Evaluation of Salient Object Detection with Fine Structures},
-                booktitle = {2021 IEEE International Conference on Image Processing (ICIP)},
                 author = {Ahmadzadeh, Azim and Kempton, Dustin J. and Chen, Yang and Angryk, Rafal A.},
+                booktitle = ICIP,
                 year = {2021},
-                doi = {10.1109/ICIP42928.2021.9506337}
             }
         """
         # The values of this collection determines the resolutions based on which MIoU is computed.
@@ -58,14 +57,6 @@ def shrink_by_grid(self, image: np.ndarray, cell_size: int) -> np.ndarray:
         return image
 
     def cal_msiou(self, pred: np.ndarray, gt: np.ndarray) -> float:
-        """
-        Args:
-            pred (np.ndarray[bool]):
-            gt (np.ndarray[bool]):
-
-        Returns:
-            float:
-        """
         pred = self.get_edge(pred)
         gt = self.get_edge(gt)
 
@@ -82,13 +73,6 @@ def cal_msiou(self, pred: np.ndarray, gt: np.ndarray) -> float:
         return msiou
 
     def step(self, pred: np.ndarray, gt: np.ndarray):
-        """
-        computes the metric for the two given regions. Use 'miou/utils/mask_loader.py'
-        to properly load masks as binary arrays for `pred` and `gt`.
-
-        :param pred: mask segmentation of the reference (ground-truth) object.
-        :param gt: mask segmentation of the target (detected) object.
-        """
         gt = gt > 128
         pred = pred > 128
 
@@ -97,7 +81,7 @@ def step(self, pred: np.ndarray, gt: np.ndarray):
         return msiou
 
     def get_results(self) -> dict:
-        """Return the results about MS-IoU.
+        """Return the results about MSIoU.
 
         :return: dict(msiou=msiou)
         """

diff --git a/readme.md b/readme.md
@@ -25,6 +25,29 @@ Your improvements and suggestions are welcome.
 
 - A Python-based salient object detection and video object segmentation evaluation toolbox. <https://github.com/lartpang/Py-SOD-VOS-EvalToolkit>
 
+### Supported Metrics
+
+| Metric                                    | Sample-based    | Whole-based | Related Class                         |
+| ----------------------------------------- | --------------- | ----------- | ------------------------------------- |
+| MAE                                       | soft            |             | `MAE`                                 |
+| S-measure $S_{m}$                         | soft            |             | `Smeasure`                            |
+| weighted F-measure ($F^{\omega}_{\beta}$) | soft            |             | `WeightedFmeasure`                    |
+| Multi-Scale IoU                           | bin             |             | `MSIoU`                               |
+| E-measure ($E_{m}$)                       | max,avg,adp     |             | `Emeasure`                            |
+| F-measure (old) ($F_{beta}$)              | max,avg,adp     |             | `Fmeasure`                            |
+| F-measure (old) ($F_{beta}$, $F_{1}$)     | max,avg,adp,bin | bin         | `FmeasureV2`+`FmeasureHandler`        |
+| BER                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`BERHandler`             |
+| Dice                                      | max,avg,adp,bin | bin         | `FmeasureV2`+`DICEHandler`            |
+| FPR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`FPRHandler`             |
+| IoU                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`IOUHandler`             |
+| Kappa                                     | max,avg,adp,bin | bin         | `FmeasureV2`+`KappaHandler`           |
+| Overall Accuracy                          | max,avg,adp,bin | bin         | `FmeasureV2`+`OverallAccuracyHandler` |
+| Precision                                 | max,avg,adp,bin | bin         | `FmeasureV2`+`PrecisionHandler`       |
+| Recall                                    | max,avg,adp,bin | bin         | `FmeasureV2`+`RecallHandler`          |
+| Sensitivity                               | max,avg,adp,bin | bin         | `FmeasureV2`+`SensitivityHandler`     |
+| Specificity                               | max,avg,adp,bin | bin         | `FmeasureV2`+`SpecificityHandler`     |
+| TNR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`TNRHandler`             |
+| TPR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`TPRHandler`             |
 ## TODO List
 
 - [x] Speed up the calculation of Emeasure.
@@ -46,20 +69,15 @@ matlab: Smeasure:0.903; wFmeasure:0.558; MAE:0.037; adpEm:0.941; meanEm:0.957; m
 
 ## Usage
 
-### ~~Download the file as your script~~ (Not Recommended)
-
 The core files are in the folder `py_sod_metrics`.
 
-### Install it as a python package. (Recommended)
-
-```shell script
-pip install pysodmetrics
-```
+- **[Latest, but may be unstable]** Install from the source code: `pip install git+https://github.com/lartpang/PySODMetrics.git`
+- **[More stable]** Install from PyPI: `pip install pysodmetrics`
 
 ### Examples
 
-- <examples/test_metrics.py>
-- <examples/metric_recorder.py>
+- [examples/test_metrics.py](./examples/test_metrics.py)
+- [examples/metric_recorder.py](./examples/metric_recorder.py)
 
 ## Reference
 
@@ -108,4 +126,11 @@ pip install pysodmetrics
   pages={248--255},
   year={2014}
 }
+
+@inproceedings{MSIoU,
+    title = {Multiscale IOU: A Metric for Evaluation of Salient Object Detection with Fine Structures},
+    author = {Ahmadzadeh, Azim and Kempton, Dustin J. and Chen, Yang and Angryk, Rafal A.},
+    booktitle = ICIP,
+    year = {2021},
+}
 ```
diff --git a/readme_zh.md b/readme_zh.md
@@ -25,6 +25,30 @@
 
 - A Python-based salient object detection and video object segmentation evaluation toolbox. <https://github.com/lartpang/Py-SOD-VOS-EvalToolkit>
 
+### 支持的指标
+
+| Metric                                    | Sample-based    | Whole-based | Related Class                         |
+| ----------------------------------------- | --------------- | ----------- | ------------------------------------- |
+| MAE                                       | soft            |             | `MAE`                                 |
+| S-measure $S_{m}$                         | soft            |             | `Smeasure`                            |
+| weighted F-measure ($F^{\omega}_{\beta}$) | soft            |             | `WeightedFmeasure`                    |
+| Multi-Scale IoU                           | bin             |             | `MSIoU`                               |
+| E-measure ($E_{m}$)                       | max,avg,adp     |             | `Emeasure`                            |
+| F-measure (old) ($F_{beta}$)              | max,avg,adp     |             | `Fmeasure`                            |
+| F-measure (old) ($F_{beta}$, $F_{1}$)     | max,avg,adp,bin | bin         | `FmeasureV2`+`FmeasureHandler`        |
+| BER                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`BERHandler`             |
+| Dice                                      | max,avg,adp,bin | bin         | `FmeasureV2`+`DICEHandler`            |
+| FPR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`FPRHandler`             |
+| IoU                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`IOUHandler`             |
+| Kappa                                     | max,avg,adp,bin | bin         | `FmeasureV2`+`KappaHandler`           |
+| Overall Accuracy                          | max,avg,adp,bin | bin         | `FmeasureV2`+`OverallAccuracyHandler` |
+| Precision                                 | max,avg,adp,bin | bin         | `FmeasureV2`+`PrecisionHandler`       |
+| Recall                                    | max,avg,adp,bin | bin         | `FmeasureV2`+`RecallHandler`          |
+| Sensitivity                               | max,avg,adp,bin | bin         | `FmeasureV2`+`SensitivityHandler`     |
+| Specificity                               | max,avg,adp,bin | bin         | `FmeasureV2`+`SpecificityHandler`     |
+| TNR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`TNRHandler`             |
+| TPR                                       | max,avg,adp,bin | bin         | `FmeasureV2`+`TPRHandler`             |
+
 ## 与[范的 Matlab 代码](https://github.com/DengPingFan/CODToolbox)的比较
 
 在我们的测试中 (测试代码可见`test`文件夹下内容)，结果与 Fan 的代码一致，如下:
@@ -41,20 +65,15 @@ matlab: Smeasure:0.903; wFmeasure:0.558; MAE:0.037; adpEm:0.941; meanEm:0.957; m
 
 ## 使用
 
-### ~~下载文件为自己的脚本~~
-
 核心文件在文件夹 `py_sod_metrics` 中。
 
-### 安装成一个包
-
-```shell script
-pip install pysodmetrics
-```
+- **[新，但可能不稳定]** 从源代码安装：`pip install git+https://github.com/lartpang/PySODMetrics.git`
+- **[更稳定一些]** 从 PyPI 安装：`pip install pysodmetrics`
 
 ### 示例
 
-- <examples/test_metrics.py>
-- <examples/metric_recorder.py>
+- [examples/test_metrics.py](./examples/test_metrics.py)
+- [examples/metric_recorder.py](./examples/metric_recorder.py)
 
 ## 参考
 
@@ -103,4 +122,11 @@ pip install pysodmetrics
   pages={248--255},
   year={2014}
 }
+
+@inproceedings{MSIoU,
+    title = {Multiscale IOU: A Metric for Evaluation of Salient Object Detection with Fine Structures},
+    author = {Ahmadzadeh, Azim and Kempton, Dustin J. and Chen, Yang and Angryk, Rafal A.},
+    booktitle = ICIP,
+    year = {2021},
+}
 ```