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README.md
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README.md
@ -27,6 +27,13 @@ result = DeepFace.verify("img1.jpg", "img2.jpg")
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}
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}
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```
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```
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You can retrieve the fields of the response object easily in Python.
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```python
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print("Is verified: ", demography["verified"])
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print("Distance: ", demography["distance"])
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```
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## Face recognition models
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## Face recognition models
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Face recognition can be handled by different models. Currently, [`VGG-Face`](https://sefiks.com/2018/08/06/deep-face-recognition-with-keras/) , [`Google Facenet`](https://sefiks.com/2018/09/03/face-recognition-with-facenet-in-keras/), [`OpenFace`](https://sefiks.com/2019/07/21/face-recognition-with-openface-in-keras/) and `Facebook DeepFace` models are supported in deepface. The default configuration verifies faces with **VGG-Face** model. You can set the base model while verification as illustared below. Accuracy and speed show difference based on the performing model.
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Face recognition can be handled by different models. Currently, [`VGG-Face`](https://sefiks.com/2018/08/06/deep-face-recognition-with-keras/) , [`Google Facenet`](https://sefiks.com/2018/09/03/face-recognition-with-facenet-in-keras/), [`OpenFace`](https://sefiks.com/2019/07/21/face-recognition-with-openface-in-keras/) and `Facebook DeepFace` models are supported in deepface. The default configuration verifies faces with **VGG-Face** model. You can set the base model while verification as illustared below. Accuracy and speed show difference based on the performing model.
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@ -94,9 +101,9 @@ Analysis function returns a json object.
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Then, you can retrieve the fields of the response object easily in Python.
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Then, you can retrieve the fields of the response object easily in Python.
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```python
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```python
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import json
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print("Age: ", demography["age"])
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demography = json.loads(demography)
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print("Gender: ", demography["gender"])
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print("Age: ",demography["age"])
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print("Emotion: ", demography["dominant_emotion"])
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```
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```
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# Installation
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# Installation
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