import numpy as np
import tensorflow as tf
import gradio as gr
from huggingface_hub import from_pretrained_keras
import cv2

img_size = 28
model = from_pretrained_keras("keras-io/keras-reptile")

def read_image(image):
    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    image = tf.image.resize(images=image, size=[img_size, img_size])
    return image

def infer(model, image):
    predictions = model.predict(image)
def display_result(input_image):
    image_tensor = read_image(input_image)
    prediction_label = infer(model=model, image=image)
    return prediction_label

input = gr.inputs.Image()
examples = [["./example0.JPG"], ["./example1.JPG"]] 
title = "Few shot learning"
description = "Upload an image or select from examples to classify fashion items."


gr.Interface(display_result, input, outputs="text", examples=examples, allow_flagging=False, analytics_enabled=False,
 title=title, description=description).launch(enable_queue=True)
gr.launch()