Update README.md

README.md

@@ -1,3 +1,58 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- zs389/isic2016
+- heroza/isic2017_classification
+language:
+- en
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+base_model:
+- Sadiksmart0/unet
+- glasses/densenet201
+pipeline_tag: image-segmentation
+model-index:
+  - name: Skin-Lesion-Segmentation
+    results:
+      - task:
+          type: image-segmentation
+        dataset:
+          name: isic2016
+          type: image
+        metrics:
+          - name: accuracy
+            type: float
+            value: 98.04
+          - name: precision
+            type: float
+            value: 97.09
+          - name: IoU (jaccard index)
+            type: float
+            value: 90.86
+          - name: F1-score (dice coefficient)
+            type: float
+            value: 94.78
+      - task:
+          type: image-segmentation
+        dataset:
+          name: isic2017
+          type: image
+        metrics:
+          - name: accuracy
+            type: float
+            value: 93.06
+          - name: precision
+            type: float
+            value: 98.63
+          - name: IoU (jaccard index)
+            type: float
+            value: 89.97
+          - name: F1-score (dice coefficient)
+            type: float
+            value: 94.35
+---
+
+A precise segmentation model trained on the ISIC2016 and 2017 datasets. Throws an accuracy of 98.06% and a Jaccard Index of 90.86. Based on the U-Net architecture with a DenseNet201 backbone.