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import streamlit as st |
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import requests |
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from PIL import Image |
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from configparser import ConfigParser |
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from io import BytesIO |
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import matplotlib.pyplot as plt |
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config = ConfigParser() |
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config.read("./config.ini") |
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if config['DEFAULT']['prod'] == 'True': |
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URL = config['PRODUCTION']['URL'] |
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else: |
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URL = config['DEVELOPMENT']['URL'] |
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def run(): |
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st.title("Image Predictor") |
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with st.form(key="image_predictor"): |
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uploaded_file = st.file_uploader( |
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label="Image", accept_multiple_files=False) |
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submitted = st.form_submit_button(label="Predict") |
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if submitted: |
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if uploaded_file is not None: |
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files = {'file': uploaded_file} |
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post = requests.post(f'{URL}/predict', files=files) |
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if post.status_code == 200: |
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res = post.json() |
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st.write(f'Prediction {res["prediction"]}') |
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get = requests.get(f'{URL}/{res["similar"]}') |
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if get.status_code == 200: |
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fig, axes = plt.subplots(1,2, layout="constrained") |
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for title, image, ax in zip( |
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["Uploaded", "Similar"], |
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[Image.open(BytesIO(uploaded_file.getvalue())), |
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Image.open(BytesIO(get.content))], |
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axes.ravel()): |
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ax.imshow(image) |
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ax.set_title(title) |
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st.pyplot(fig) |
