Create app.py

app.py

@@ -1,3 +1,31 @@
-import gradio as gr
+#Loading the dependencies
+import streamlit as st
+import requests
+from io import BytesIO
+from PIL import Image
+import os
 
-gr.Interface.load("models/Hrishikesh332/autotrain-meme-classification-42897109437").launch()
+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):
+
+    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:  #To create a side bar
+    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()
+        output = query(data)
+        st.write("Predicted Output:", output)