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Sefik Ilkin Serengil 2022-07-16 11:50:48 +01:00 committed by GitHub
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@ -72,14 +72,7 @@ Face recognition models basically represent facial images as multi-dimensional v
embedding = DeepFace.represent(img_path = "img.jpg") embedding = DeepFace.represent(img_path = "img.jpg")
``` ```
This function returns an array as output. The size of the output array would be different based on the model name. For instance, VGG-Face is the default model for deepface and it represents facial images as 2622 dimensional vectors. This function returns an array as output. The size of the output array would be different based on the model name. For instance, VGG-Face is the default model for deepface and it represents facial images as 2622 dimensional vectors. Here, embedding is also plotted with 2622 slots horizontally. Each slot is corresponding to a dimension value in the embedding vector and dimension value is explained in the colorbar on the right.
```python
assert isinstance(embedding, list)
assert len(embedding) == 2622
```
Here, embedding is also plotted with 2622 slots horizontally. Each slot is corresponding to a dimension value in the embedding vector and dimension value is explained in the colorbar on the right.
<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/embedding.jpg" width="95%" height="95%"></p> <p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/embedding.jpg" width="95%" height="95%"></p>