from fastai.vision.all import * from io import BytesIO import requests import streamlit as st """ # Cat type classification This is a classifier for images of cat typpe. It was trained on simulated images. """ def predict(img): st.image(img, caption="Your image", use_column_width=True) pred, key, probs = learn_inf.predict(img) # st.write(learn_inf.predict(img)) f""" ## This **{'is ' if pred == 'mi' else 'is not'}** an MI (heart attack). ### Rediction result: {pred} ### Probability of {pred}: {probs[key].item()*100: .2f}% """ path = "./" learn_inf = load_learner(path + "model_Resnet18.pkl") option = st.radio("", ["Upload Image", "Image URL"]) if option == "Upload Image": uploaded_file = st.file_uploader("Please upload an image.") if uploaded_file is not None: img = PILImage.create(uploaded_file) predict(img) else: url = st.text_input("Please input a url.") if url != "": try: response = requests.get(url) pil_img = PILImage.create(BytesIO(response.content)) predict(pil_img) except: st.text("Problem reading image from", url)