Update README.md

README.md

@@ -254,6 +254,8 @@ However the metrics for the Challenge were calculated on 12 classes and the TEST
 #### Metrics
 
 With the evaluation protocol, the **FLAIR-INC_RVBIE_resnet34_unet_15cl_norm** have been evaluated to **OA= 76.37%** and **mIoU=54.71%**. 
+The _snow_ class is discarded from the average metrics.
+
 The following table give the class-wise metrics :
 
 | Modalities              |   IoU (%)    | Fscore (%)  | Precision (%)  | Recall (%)  |
@@ -271,18 +273,21 @@ The following table give the class-wise metrics :
 | agricultural land       |  52.01    |  68.43  |  59.18  |  81.12  |
 | plowed land             |  40.84    |  57.99  |  68.28  |  50.40  |
 | swimming_pool           |  48.44    |  65.27  |  81.62  |  54.37  |
-| snow                    |  00.00    |  00.00  |  00.00  |  00.00  |
+| _snow_                    |  _00.00_    |  _00.00_  |  _00.00_  |  _00.00_  |
 | greenhouse              |  39.45    |  56.57  |  45.52  |  74.72  |
 | ----------------------- | ----------|---------|---------|---------|
-| average                 |  54.72    |  67.60  |  69.35  |  67.66  |
+| **average**                 |  **58.63**    |  **72.44**  |  **74.3**  |  **72.49**  |
 
 <!-- These are the evaluation metrics being used, ideally with a description of why. -->
 
 {{ testing_metrics | default("[More Information Needed]", true)}}
 
+The following illustration give the confusion matrix :
+* Left : normalised acording to columns, columns sum at 100% and the **precision** is on the diagonal of the matrix
+* Right : normalised acording to rows, rows sum at 100% and the **recall** is on the diagonal of the matrix 
 
 
-| <div style="width:290px">Confusion Matrix (precision)</div> |<div style="width:290px">Confusion Matrix (recall)</div>  |
+| <div style="width:290px">Normalised confusion Matrix (precision)</div> |<div style="width:290px">Normalised Confusion Matrix (recall)</div>  |
 | --------------------------------------- | ------------------------------------- |
 | `<img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-precision.png" alt="drawing" style="width:300px;"/> |`<img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-recall.png" alt="drawing" style="width:300px;"/>  |