github/deepface
1
1
Fork 0
mirror of https://github.com/serengil/deepface.git synced 2025-06-07 12:05:22 +00:00
Code Issues Packages Projects Releases Wiki Activity

represent

Browse Source
This commit is contained in:
Sefik Ilkin Serengil 2021-04-11 14:40:27 +03:00 committed by GitHub
parent b0f152ab31
commit 571326890a
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
README.md
View File

@ -83,14 +83,14 @@ Euclidean L2 form [seems](https://youtu.be/i_MOwvhbLdI) to be more stable than c
**Tech Stack** - [`Vlog`](https://youtu.be/R8fHsL7u3eE)
<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/tech-stack.png" width="90%" height="90%"></p>
The question is that where to store facial representations. You can find vector embeddings of facial images with the represent function.
```python
embedding = DeepFace.represent("img.jpg", model_name = 'Facenet')
```
<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/tech-stack.png" width="90%" height="90%"></p>
Recommended tech stack for face verification is mainly based on [relational databases and regular SQL](https://sefiks.com/2021/02/06/deep-face-recognition-with-sql/) or key-value stores such as [Redis](https://sefiks.com/2021/03/02/deep-face-recognition-with-redis/) or [Cassandra](https://sefiks.com/2021/01/24/deep-face-recognition-with-cassandra/). Herein, key-value stores overperform than regular relational databases.
Face verification is a subset of face recognition. In other words, you can run any face verification tool for face recognition as well. However, face verification has O(1) and face recognition has O(n) time complexity. That's why, face recognition becomes problematic with regular face verification tools on millions/billions level data and limited hardware.