Update README.md

README.md

@@ -12,6 +12,8 @@ We present EdgeFace- a lightweight and efficient face recognition network inspir
 
 * **Training**: EdgeFace-Base was trained on [Webface260M](https://www.face-benchmark.org/) dataset (12M and 4M subsets)
 * **Parameters**: 18.23M
+* **Task**: Efficient Face Recognition Model for Edge Devices
+* **Framework**: Pytorch
 * **Output structure**: Batch of face images
 
 ## Evaluation of EdgeFace
@@ -44,7 +46,7 @@ We present EdgeFace- a lightweight and efficient face recognition network inspir
 |**Edgeface_Base (ours)**      | 18.23   | 1398.83   | 99.83 ± 0.24 | 96.07 ± 1.03 | 93.75 ± 1.16 | 97.01 ± 0.94 | 97.60 ± 0.70 |-          | -         |
 
 
-#### Performance benchmarks of different variants of **EdgeFace**:
+### Performance benchmarks of different variants of **EdgeFace**:
 
 | Model                   | MPARAMS | MFLOPs  | LFW (%)        | CALFW (%)      | CPLFW (%)      | CFP-FP (%)     | AgeDB30 (%)    |
 |-------------------------|---------|---------|----------------|----------------|----------------|----------------|----------------|
@@ -54,16 +56,48 @@ We present EdgeFace- a lightweight and efficient face recognition network inspir
 | edgeface_xxs            | 1.24    | 94.72   | 99.57 ± 0.33   | 94.83 ± 0.98   | 90.27 ± 0.93   | 93.63 ± 0.99   | 94.92 ± 1.15   |
 
 
-
 ## Running EdgeFace-Base
 
+* Minimal code to instantiate the model and perform inference:
+``` bash
+    import torch
+    from torchvision import transforms
+    from face_alignment import align
+    from backbones import get_model
+
+    # load model
+    model_name="edgeface_base"
+    model=get_model(model_name)
+    checkpoint_path=f'checkpoints/{arch}.pt'
+    model.load_state_dict(torch.load(checkpoint_path, map_location='cpu')).eval()
+
+    transform = transforms.Compose([
+                transforms.ToTensor(),
+                transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5]),
+                ])
+
+    path = 'path_to_face_image'
+    aligned = align.get_aligned_face(path) # align face
+    transformed_input = transform(aligned) # preprocessing
+
+    # extract embedding
+    embedding = model(transformed_input)
+```
+
+
 Please check the project [GitHub repository](https://gitlab.idiap.ch/bob/bob.paper.tbiom2023_edgeface/)
 
 ## License
 
 EdgeFace is released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en)
 
+## Copyright 
+
+(c) 2024, Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza,  Ketan Kotwal, Sébastien Marcel Idiap Research Institute, Martigny 1920, Switzerland.
+
+https://gitlab.idiap.ch/bob/bob.paper.tbiom2023_edgeface/-/blob/master/LICENSE
 
+Please refer to the link for information about the License & Copyright terms and conditions.
 
 ## Citation