create-app.py

app.py

@@ -0,0 +1,31 @@
+#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()