|
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""" |
|
## 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 + "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) |
|
|
