Delete app.py

app.py

@@ -1,46 +0,0 @@
-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)
-    # 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 + "resnet50_stage-2(1).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)
-