Upload 3 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+my_cnn_model.keras filter=lfs diff=lfs merge=lfs -text

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 
+
+st.title("Skin Cancer Image Classification")
+st.write("Upload an image and let the model guess whether it is a cancer or not.")
+
+model = load_model("my_cnn_model.keras")
+
+def process_image(img):
+    img = img.resize((170,170)) # set the size as 170 x 170 pixel
+    img = np.array(img)
+    img = img / 255.0 # normalized
+    img = np.expand_dims(img, axis=0)
+    return img
+
+
+file = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+if file is not None:
+    img = Image.open(file)
+    st.image(img, caption="Uploaded Image")
+    image = process_image(img)
+
+    prediction = model.predict(image)
+    predicted_class = np.argmax(prediction)
+
+    class_names = ["It is NOT Cancer!", "It is Cancer!"]
+    st.write(class_names[predicted_class])

my_cnn_model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2a9c7220d74b23b0acad9db9df93676548ff873445060d0c7283a471d9e8a6c5
+size 165518887

requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+tensorflow