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#ALL as a whole
import os
import gradio as gr
from deepface import DeepFace
import matplotlib.pyplot as plt
model_name = 'ArcFace' #VGG-Face, Facenet, OpenFace, DeepFace, DeepID, Dlib, ArcFace or Ensemble
def get_deepface_verify(img1_path, img2_path, model_name):
img1_detect= DeepFace.detectFace(img1_path)
img2_detect= DeepFace.detectFace(img2_path)
result = DeepFace.verify(img1_path=img1_path,img2_path=img2_path,model_name = model_name)
return result
title = "DeepFace"
description = "Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, ArcFace and Dlib."
examples=[["10Jan_1.jpeg"],["10Jan_2.jpeg"]]
facial_attribute_demo = gr.Interface(get_deepface_verify, inputs = ["image","image"],outputs="json",title=title,
description=description,enable_queue=True,examples=[["10Jan_1.jpeg"]],cache_examples=False)
#########################3
from Deepface_analyze import facial_attribute_demo
facial_attribute_demo.launch(debug=True)
####################
demo = gr.TabbedInterface([facial_attribute_demo , facial_attribute_demo], ["Deepface-Verify","Deepface-analyze"])
if __name__ == "__main__":
demo.launch()
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