Update README.md

README.md

@@ -224,14 +224,15 @@ The FLAIR-INC_RVBIE_resnet34_unet_15cl_norm model was trained on a HPC/AI resour
 FLAIR-INC_RVBIE_resnet34_unet_15cl_norm was obtained for num_epoch=76 with corresponding val_loss=0.56. 
 
 
-<div style="position: relative; text-align center;">
-    <p>TRAIN loss</p>
-    <img src="train_loss_FLAIR-INC_RGBIE_resnet34_unet_15cl_norm.png" alt="drawing" style="width: 60%;"/>
-    <p>VALIDATION loss</p>
-    <img src="val_loss_FLAIR-INC_RGBIE_resnet34_unet_15cl_norm.png" alt="drawing" style="width: 60%;"/>
+<div style="position: relative; text-align: center;">
+    <p style="margin: 0;">TRAIN loss</p>
+    <img src="train_loss_FLAIR-INC_RGBIE_resnet34_unet_15cl_norm.png" alt="TRAIN loss" style="width: 60%; display: block; margin: 0 auto;"/>
+    <p style="margin: 0;">VALIDATION loss</p>
+    <img src="val_loss_FLAIR-INC_RGBIE_resnet34_unet_15cl_norm.png" alt="VALIDATION loss" style="width: 60%; display: block; margin: 0 auto;"/>
 </div>
 
 
+
 ## Evaluation
 
 ### Testing Data, Factors & Metrics
@@ -285,9 +286,9 @@ The following illustration gives the resulting confusion matrix :
 
 <div style="position: relative; text-align center;">
     <p>Normalized Confusion Matrix (precision)</p>
-    <img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-precision.png" alt="drawing" style="width: 70%;"/>
+    <img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-precision.png" alt="drawing" style="width: 70%; display: block; margin: 0 auto;"/>
     <p>Normalized Confusion Matrix (recall)</p>
-    <img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-recall.png" alt="drawing" style="width: 70%;"/>
+    <img src="FLAIR-INC_RVBIE_resnet34_unet_15cl_norm_cm-recall.png" alt="drawing" style="width: 70%; display: block; margin: 0 auto;"/>
 </div>