app.py

import tensorflow as tf
import gradio as gr

json_file=open(r"dark_s.json","r")
loaded_model_json=json_file.read()
json_file.close()
loaded_model= tf.keras.models.model_from_json(loaded_model_json)
loaded_model.load_weights("dark_s.h5")

json_file=open(r"eyes_d.json","r")
loaded_model_json=json_file.read()
json_file.close()
loaded_model1 = tf.keras.models.model_from_json(loaded_model_json)
loaded_model1.load_weights("eyes_d.h5")

json_file=open(r"wrinkl.json","r")
loaded_model_json=json_file.read()
json_file.close()
loaded_model2 = tf.keras.models.model_from_json(loaded_model_json)
loaded_model2.load_weights("wrinkl.h5")

def classifier(Imgarr):
    l = []
    img = Imgarr.reshape(-1, 50, 50, 3)
    result = loaded_model.predict(img)
    result = result[0]
    if result[0] >= result[1]:
        l.append("dark spots")
    else:
        l.append("no dark spots")

    result = loaded_model1.predict(img)
    result = result[0]
    if result[0] >= result[1]:
        l.append("no puffy eyes")
    else:
        l.append("puffy eyes")

    result = loaded_model2.predict(img)
    result = result[0]
    if result[0] >= result[1]:
        l.append("no wrinkles on face")
    else:
        l.append("wrinkles on face")

    return "The Predictions are " + str(l)

interface = gr.Interface(classifier,gr.inputs.Image(shape=(50,50)),outputs = "text",
                          description="Classifier of Aging Signs of Images",
                          title="Aging Signs Classifier",
                          examples=[['42.jpg'],['778.jpg'],['1836.png'],['71.jpg'],['56.jpg']])
interface.launch()