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#ALL as a whole
import os
import gradio as gr
from deepface import DeepFace
import matplotlib.pyplot as plt
def get_deepface_verify(img1_detect, img2_detect ):
img1_detect= DeepFace.detectFace(img1_path)
img2_detect= DeepFace.detectFace(img2_path)
model_name = 'ArcFace' #VGG-Face, Facenet, OpenFace, DeepFace, DeepID, Dlib, ArcFace or Ensemble
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,["image","image", label="distance metric"],[gr.outputs.Label(label="same person"),gr.outputs.Label(label="distance"),gr.outputs.Label(label="max threshold to verify"),gr.outputs.Label(label="model"),gr.outputs.Label(label="similarity metric")],enable_queue=True,examples=examples, title=title,description=description,article=article,theme="darkdefault").launch(debug=True)
facial_attribute_demo.launch()
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