app.py

#import tensorflow_addons as tfa
import gradio as gr
import tensorflow as tf
import numpy as np
from tensorflow.keras.models import load_model
import tensorflow_addons as tfa
import os

#os.environ['TF_KERAS'] = '1'
#os.environ['TF_ENABLE_ONEDNN_OPTS']='0'

labels=['Burger King', 'Subway', 'McDonalds', 'Starbucks', 'Other', 'KFC']
HEIGHT,WIDTH=224,224
model=load_model('best_model.h5')
NUM_CLASSES=6


def classify_image(inp):
  inp = inp.reshape((-1, HEIGHT,WIDTH, 3))
  inp = tf.keras.applications.nasnet.preprocess_input(inp) 
  prediction = model.predict(inp).flatten()
  return {labels[i]: float(prediction[i]) for i in range(NUM_CLASSES)}

image = gr.Image(shape=(HEIGHT,WIDTH),label='Input')
label = gr.Label()

gr.Interface(fn=classify_image, inputs=image, outputs=label, title='Brand Logo Detection').launch(debug=False)