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import streamlit as st
import requests
from PIL import Image
from io import BytesIO
CLASS_LABELS = {
0: "airplane",
1: "bird",
2: "car",
3: "cat",
4: "deer",
5: "dog",
6: "horse",
7: "monkey",
8: "ship",
9: "truck",
}
def get_classification(image_bytes):
response = requests.post("http://localhost:5000/classify", files={"file": image_bytes})
class_id = response.json()["classification"]
return CLASS_LABELS[class_id]
st.title("Image Classification")
st.write("Upload an image to classify")
uploaded_file = st.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
if st.button("Classify"):
img_bytes = uploaded_file.read()
label = get_classification(img_bytes)
st.write("Prediction:", label)
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