Upload 3 files

app.py

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+import streamlit as st
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+model = load_model("my_cnn_model.h5")
+
+
+def process_image(img):
+    img = img.resize((170,170))
+    img = np.array(img)
+    img = img/255.0
+    img = np.expand_dims(img,axis=0)
+    return img
+
+
+st.title("Image Classification - Cancer Classification :cancer: ")
+st.write("Upload an image and the models predicts if it is cancer")
+
+file = st.file_uploader("Select an image",type=["jpg","jpeg","png"])
+
+if file is not None:
+    img = Image.open(file)
+    st.image(img,caption="Uploaded picture")
+    img = process_image(img)
+    prediction = model.predict(img)
+    predicted_class = np.argmax(prediction)
+
+    class_names = ["Non Cancer","Cancer"]
+    st.write(class_names[predicted_class])

my_cnn_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aa1548c44f128bb4e182ef9ce23763e14906f58bc1df02e7f3598b944625945a
+size 165525592

requirements.txt

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+streamlit
+tensorflow