| from fastai.vision.all import * |
| from io import BytesIO |
| import requests |
| import streamlit as st |
|
|
| """ |
| # HeartNet |
| This is a classifier for images of 12-lead EKGs. It will attempt to detect whether the EKG indicates an acute MI. 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) |
| |
|
|
| f""" |
| ## 圖片預測結果 **{'錯誤' if pred == '==' else '是'}**... |
| ### Rediction result: {pred} |
| ### Probability of {pred}: {probs[key].item()*100: .2f}% |
| """ |
|
|
|
|
| path = "./" |
| learn_inf = load_learner(path + "demo_model.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) |
| |
