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@ -45,14 +45,16 @@ Items of resp_obj might be unsorted when you pass multiple instances to verify f
**Large scale face recognition** - [`Demo`](https://youtu.be/Hrjp-EStM_s)
You can apply face recognition on a large scale data set as well. Vector representations of faces in your database folder stored in a pickle file when find function is called once. Then, deepface just finds vector representation of the target image. Finding an identity in a large scale data set will be performed in just seconds.
You can apply face recognition on a large scale data set as well. Face recognition requires to apply face verification multiple times. Herein, deepface offers an out-of-the-box find function to handle this action. Representations of faces photos in your database folder will be stored in a pickle file when find function is called once. Then, deepface just finds representation of the target image. In this way, finding an identity in a large scale data set will be performed in just seconds.
```python
from deepface import DeepFace
import pandas as pd
df = DeepFace.find(img_path = "img1.jpg", db_path = "C:/workspace/my_db")
print(df.head())
#DeepFace.find(img_path = ["img1.jpg", "img2.jpg"], db_path = "C:/workspace/my_db")
#dfs = DeepFace.find(img_path = ["img1.jpg", "img2.jpg"], db_path = "C:/workspace/my_db")
```
**Supported face recognition models**