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Update app.py
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app.py
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import streamlit as st
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from datasets import load_dataset, Image
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from huggingface_hub import
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pip install joblib
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import joblib
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REPO_ID = "jableable/road_project"
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FILENAME = "best_model.keras"
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model = joblib.load(
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hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
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)
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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loaded_model = keras.saving.load_model("best_model.keras")
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dataset = load_dataset("beans", split="train")
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import streamlit as st
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from datasets import load_dataset, Image
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from huggingface_hub import from_pretrained_keras
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x = st.slider('Select a value')
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st.write(x, 'squared is', x * x)
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#loaded_model = keras.saving.load_model("best_model.keras")
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model = from_pretrained_keras("best_model.keras")
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prediction = model.predict(image)
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prediction = tf.squeeze(tf.round(prediction))
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print(f'The image is a {classes[(np.argmax(prediction))]}!')
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dataset = load_dataset("beans", split="train")
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