import tensorflow.compat.v2 as tf
import tensorflow_hub as hub
import numpy as np
import pandas as pd
import cv2
from skimage import io

m = hub.KerasLayer('https://tfhub.dev/google/aiy/vision/classifier/food_V1/1')

labelmap_url = "https://www.gstatic.com/aihub/tfhub/labelmaps/aiy_food_V1_labelmap.csv"
input_shape = (224, 224)

def classify_image(inp):
    inp = inp.reshape((-1, 224, 224, 3))
    output = m(images)
    predicted_index = output.numpy().argmax()
    classes = list(pd.read_csv(labelmap_url)["name"])
    return {labels[i]: float(prediction[i]) for i in range(1000)}
    
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label(num_top_classes=3)

gr.Interface(
    fn=classify_image,
    inputs=image,
    outputs=label,
    examples=[["isachertorte.png"], ["sandwich.jpg"]],
).launch()