app.py

import streamlit as st
import requests
from io import BytesIO
from PIL import Image
import os

api_key = os.environ['API_KEY']

API_URL = "https://api-inference.huggingface.co/models/Hrishikesh332/autotrain-meme-classification-42897109437"
headers = {"Authorization": f"Bearer {api_key}"}

def query(data : bytes):
    # with open(filename, "rb") as f:
    #     data = f.read()
    response = requests.post(API_URL, headers=headers, data=data)
    return response.json()



st.markdown("<h1 style='text-align: center;'>Memeter 💬</h1>", unsafe_allow_html=True)
st.markdown("---")
with st.sidebar:
    st.title("Memometer")
    st.caption('''
    Memeter is an application used for the classification of whether the images provided is meme or not meme
    ''', unsafe_allow_html=False)

img = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])

    
if img is not None:
        
        data = img.read()
        st.image(data)
        output = query(data)
        st.write("Predicted Output:", output)