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Sefik Ilkin Serengil 2020-06-10 09:31:14 +03:00 committed by GitHub
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@ -25,7 +25,6 @@ Verification function under the DeepFace interface offers a single face recognit
```python
from deepface import DeepFace
result = DeepFace.verify("img1.jpg", "img2.jpg")
print("Is verified: ", result["verified"])
```
@ -50,10 +49,7 @@ You can apply face recognition on a [large scale](https://sefiks.com/2020/05/25/
```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())
#dfs = DeepFace.find(img_path = ["img1.jpg", "img2.jpg"], db_path = "C:/workspace/my_db")
```
@ -111,10 +107,8 @@ Deepface also offers facial attribute analysis including [`age`](https://sefiks.
```python
from deepface import DeepFace
demography = DeepFace.analyze("img4.jpg") #passing nothing as 2nd argument will find everything
#demography = DeepFace.analyze("img4.jpg", ['age', 'gender', 'race', 'emotion']) #identical to the line above
demography = DeepFace.analyze("img4.jpg", actions = ['age', 'gender', 'race', 'emotion'])
#demographies = DeepFace.analyze(["img1.jpg", "img2.jpg", "img3.jpg"]) #analyzing multiple faces same time
print("Age: ", demography["age"])
print("Gender: ", demography["gender"])
print("Emotion: ", demography["dominant_emotion"])
@ -137,13 +131,11 @@ You can build facial attribute analysis models once and pass these to analyze fu
```python
import json
from deepface.extendedmodels import Age, Gender, Race, Emotion
models = {}
models["emotion"] = Emotion.loadModel()
models["age"] = Age.loadModel()
models["gender"] = Gender.loadModel()
models["race"] = Race.loadModel()
DeepFace.analyze("img1.jpg", models=models)
```