Create app.py

application file

app.py

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+import streamlit as st
+import torch
+from torchvision import models
+from PIL import Image
+from util import classify, set_background
+
+
+st.title('Chest X-Ray Pneumonia Detector')
+
+st.header('Please upload a chest X-ray image.')
+
+file = st.file_uploader('-', type=['jpeg', 'jpg', 'png'])
+
+# load classifier
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model = models.resnet18(weights=False)
+num_ftrs = model.fc.in_features
+model.fc = torch.nn.Linear(num_ftrs, 2)  # binary classification
+model.load_state_dict(torch.load('./resnet18.pth', map_location=device))
+model.to(device)
+model.eval()
+
+# load class names
+# class_names = ['Normal', 'Pneumonia']
+with open('./labels.txt', 'r') as f:
+    class_names = [a[:-1].split(' ')[1] for a in f.readlines()]
+    f.close()
+
+# display image
+if file is not None:
+    image = Image.open(file).convert('RGB')
+    st.image(image, use_column_width=True)
+
+    # classify image
+    class_name, conf_score = classify(image, model, class_names)
+
+    # write classification
+    st.write("## {}".format(class_name))
+    st.write("### Confidence: {:.2f}%".format(conf_score * 100))
+
+set_background('./background.jpg')
+# Footer
+footer = """
+<div style="position: fixed; bottom: 0; width: 100%; background-color: #EDF3FA; padding: 10px; text-align: center;">
+      Created by Imran Nawar
+</div>
+"""
+st.markdown(footer, unsafe_allow_html=True)