Update README.md

README.md

@@ -1,27 +1,47 @@
 ---
 language:
 - en
+metrics:
+- accuracy
+pipeline_tag: image-classification
+tags:
+- arxiv:1512.03385
 ---
 
-## Resnet50-v1.5
+# Resnet50-v1.5
 
 - Origin: https://github.com/mlcommons/inference/tree/master/vision/classification_and_detection
 - Note : https://catalog.ngc.nvidia.com/orgs/nvidia/resources/resnet_50_v1_5_for_pytorch
-- Article: https://arxiv.org/abs/1512.03385
-- Input:
-    - size: \[N, 3, 224, 224\]
-    - format : NCHW
+
+## Model
+
 - ONNX attributes:
-	- opset : 11
-	- Operators: 233 (11 types)
-		- Add: 17
-		- ArgMax: 1
-		- Conv2D: 36
-		- MatMul: 1
-		- PaddedConv2D: 17
-		- PaddedMaxPooling2D: 1
-		- Producer: 108
-		- ReLU: 49
-		- ReduceMean: 1
-		- Softmax: 1
-		- Squeeze: 1
+  - opset : 11
+  - Operators: 233 (11 types)
+    - Add: 17
+    - ArgMax: 1
+    - Conv2D: 36
+    - MatMul: 1
+    - PaddedConv2D: 17
+    - PaddedMaxPooling2D: 1
+    - Producer: 108
+    - ReLU: 49
+    - ReduceMean: 1
+    - Softmax: 1
+    - Squeeze: 1
+
+## Aidge support
+
+> Note: We tested this network for the following features. If you encounter any error please open an [issue](https://gitlab.eclipse.org/groups/eclipse/aidge/-/issues). Features not tested in CI may not be functional.
+
+|   Feature   | Tested in CI |
+| :---------: | :----------: |
+| ONNX import |      ✔       |
+| Backend CPU |      ✔       |
+
+## ImageNet1k
+- Input:
+  - size: \[N, 3, 224, 224\]
+  - format : NCHW
+- Output
+  - size: [N, 1000]