import tensorflow as tf
from tensorflow.keras.models import load_model
import gradio as gr
import numpy as np
import cv2

model = load_model("model_1.h5")

labels = ["zero","one","two","three","four","five","six","seven","eight","nine","ten","eleven","twelve","thrteen","fourteen","fifteen","sixteen","seventeen","eightteen","nineteen"]

def predict(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    resized = cv2.resize(gray, (64, 64))
    reshaped = resized.reshape(1, 64, 64, 1)
    out = model.predict(reshaped)
    cls = labels[out.argmax()]
    return cls

ui = gr.Interface(
fn=predict,
inputs=gr.Image(type="numpy"),
outputs=gr.Textbox()
)