Create app.py

app.py

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+#IMPORTANT PART ONLY
+#!pip install deepface
+import gradio as gr
+
+from deepface import DeepFace
+#from google.colab import drive
+#drive.mount('/content/drive')
+#img1_path = '/content/drive/My Drive/Colab Notebooks/DeepLearning/FaceRecognition/PhotoDataSet/10Jan_1.jpeg'
+import zipfile
+with zipfile.ZipFile("PhotoDataSet.zip","r") as zip_ref:
+    zip_ref.extractall("db_path")
+
+#db_path='/content/drive/My Drive/Colab Notebooks/DeepLearning/FaceRecognition/PhotoDataSet/'
+
+import pandas as pd
+def get_deepface(image):
+
+    df = DeepFace.find(img_path=image, db_path=db_path)
+    #print(df.head())
+    return DeepFace.analyze(img_path=img1_path))
+
+
+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."
+
+facial_attribute_demo = gr.Interface(
+    fn=process_document,
+    inputs="image",
+    outputs="json",
+    title="face recognition and facial attribute analysis (age, gender, emotion and race) framework",
+    description=description,
+    
+    enable_queue=True,
+    examples=[["10Jan_1.jpeg"]],
+    cache_examples=False)
+
+facial_attribute_demo .launch()