app.py

import gradio as gr
from huggingface_hub import login, from_pretrained_keras
import os
import numpy as np
import cv2

login(os.environ["HF_TOKEN"])

model = from_pretrained_keras("elsamueldev/cats-dogs")


def preprocess(img: np.array) -> np.array:
    img = cv2.resize(img, (100, 100)) # resize to 100x100
    img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # convert to grayscale
    img = img.reshape(100, 100, 1) # reshape to 100x100x1
    img = img / 255 # normalize
    img = np.array([img]) # reshape to 1x100x100x1

    return img

def predict(img: np.array):
    img = preprocess(img)

    dog = model.predict(img)[0][0]
    cat = 1 - dog

    return {"dog": dog, "cat": cat}

gr.Interface(
    fn=predict,
    inputs="image",
    outputs="label"
).launch()