dvc-streamlit-article-python-11.py

from PIL import Image

model = load_model(rev=selected_commit.hexsha)
uploaded_file = st.file_uploader("Upload an image")

if uploaded_file:
    image = Image.open(uploaded_file)
    image_name = uploaded_file.name
    resized_image = image.resize(IMG_SIZE)

    input = np.expand_dims(
        tf.keras.preprocessing.image.img_to_array(resized_image),
        axis=0,
    )

    if st.button("Run model"):
        prediction = tf.nn.sigmoid(model.predict(input).flatten()).numpy()[0]

        st.dataframe(pd.DataFrame([{
            "commit_hash": selected_commit.hexsha,
            "cat": 1 - prediction,
            "dog": prediction,
        }]))