Upload app.py

app.py

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+import streamlit as st
+from PIL import Image
+import numpy as np
+import tensorflow as tf
+from huggingface_hub import from_pretrained_keras
+
+model = from_pretrained_keras('Emmawang/mobilenet_v2_fake_image_detection')
+
+# Define the Streamlit app
+def main():
+    st.title("Fake Image Detection")
+    st.write("This is a demo of a fake image detection app using a MobileNetV2 model trained on the Fake Image Detection dataset.")
+    st.write("Upload an image to see if it's fake or not.")
+    st.write("")
+
+    uploaded_file = st.file_uploader("Choose an image...", type="png")
+    if uploaded_file is not None:
+
+        img = Image.open(uploaded_file).resize([128, 128])
+        img = np.array(img).astype(np.float32)
+        img = img/255
+        img = img.reshape(-1, 128, 128, 3)
+        result = get_prediction(img, model)
+        if result > 0.5:
+            st.write("This image is fake.")
+        else:
+            st.write("This image is real.")
+
+
+def get_prediction(image, model):
+    prediction = model.predict(image)
+    return np.argmax(prediction)
+
+if __name__ == '__main__':
+    main()
+