Upload 3 files

app.py

@@ -0,0 +1,54 @@
+import streamlit as st
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+# Load the model
+model = load_model('cnn_model.h5', compile=False)
+
+# Function to process the uploaded image
+def process_image(img):
+    img = img.resize((128, 128))
+    img = np.array(img)
+    img = img / 255.0
+    img = np.expand_dims(img, axis=0)
+    return img
+
+# Title of the application
+st.title('👶 Age Detection from Image 📸')
+st.write("Upload a photo, and the model will predict the age.")
+
+# Sidebar for additional interaction options
+st.sidebar.header("Instructions")
+st.sidebar.write("""
+1. Upload an image of a face.
+2. The model will predict the age based on the image.
+3. The output will be displayed below the image.
+""")
+
+# File uploader for the user to upload an image
+file = st.file_uploader('Select an image (jpg, jpeg, png)', type=['jpg', 'jpeg', 'png'])
+
+if file is not None:
+    # Displaying the uploaded image
+    img = Image.open(file)
+    st.image(img, caption='Uploaded Image', use_column_width=True)
+    
+    # Process the image and predict the result
+    image = process_image(img)
+    prediction = model.predict(image)
+    prediction = np.round(prediction).astype(int)  # Rounding the prediction
+
+    # Show result in a more interactive format
+    st.subheader("Prediction Result:")
+    st.write(f"Predicted Age: **{prediction[0][0]}** years old")
+
+    # Optionally, you can add a confidence message
+    st.markdown(f"""
+    **Confidence:** The model has made this prediction based on its trained data, but the prediction may vary depending on the quality of the image and other factors.
+    """)
+
+    # A divider for clarity
+    st.markdown("---")
+else:
+    st.write("Please upload an image to get started.")

cnn_model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:245aecb3416a5808c9d86e676a79737c3d3060e4a8b0bd5e0e37d58b78294ac7
+size 83915432

requirements.txt

@@ -0,0 +1,3 @@
+streamlit
+tensorflow
+Pillow