This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision | ||
|
products:sbc:edge2:npu:demos:facenet [2023/09/19 22:40] louis |
products:sbc:edge2:npu:demos:facenet [2025/04/09 23:38] (current) louis |
||
|---|---|---|---|
| Line 3: | Line 3: | ||
| ====== FaceNet PyTorch Edge2 Demo - 6 ====== | ====== FaceNet PyTorch Edge2 Demo - 6 ====== | ||
| - | ===== Get Source Code ===== | + | {{indexmenu_n> |
| + | |||
| + | ===== Introduction ===== | ||
| + | |||
| + | FaceNet is a face recognition model. It will convert a face image into a feature map. Compare the feature map between image and face database. Here are two judgment indicators, cosine similarity and Euclidean distance. The closer the cosine similarity is to 1 and the closer the Euclidean distance is to 0, the more similar is between two faces. | ||
| + | |||
| + | Here takes **lin_1.jpg** as example. Inference results on Edge2. | ||
| + | |||
| + | {{: | ||
| + | |||
| + | ===== Train Model ===== | ||
| The codes we use [[gh> | The codes we use [[gh> | ||
| Line 134: | Line 144: | ||
| ==== Get source code ==== | ==== Get source code ==== | ||
| - | Clone the source code form our [[gh> | + | Clone the source code from our [[gh> |
| ```shell | ```shell | ||