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CNN_Prak4_ML.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:fd8b10e96ef8fa2e2d16c3251e2b21d6d9ea0942dcaea4941ee632dcce219f4c
+size 1781096

app.py

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+import streamlit as st
+import tensorflow as tf
+from tensorflow.keras.preprocessing.image import load_img, img_to_array
+import numpy as np
+from PIL import Image
+import io
+
+st.set_page_config(
+    page_title="Waste Classifier",
+    layout="centered"
+)
+
+@st.cache_resource
+def load_model():
+    return tf.keras.models.load_model('CNN_Prak4_ML.h5')
+
+def preprocess_image(img):
+    img = img.resize((244, 244))
+    img = img_to_array(img)
+    img = np.expand_dims(img, axis=0)
+    img = img / 255.0
+    return img
+
+LABEL_CLASS = {
+    0: "Cardboard",
+    1: "Glass",
+    2: "Metal",
+    3: "Paper",
+    4: "Textile Trash",
+    5: "Vegetation"
+}
+
+
+def main():
+    st.title("Waste Classifier")
+    st.write("Upload an image and the model will predict waste image")
+    
+    uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+    
+    if uploaded_file is not None:
+        image = Image.open(uploaded_file)
+        st.image(image, caption='Uploaded Image', use_column_width=True)
+        
+        if st.button('Predict'):
+            model = load_model()
+            
+            processed_image = preprocess_image(image)
+            
+            with st.spinner('Predicting...'):
+                prediction = model.predict(processed_image)
+                pred_class = LABEL_CLASS[np.argmax(prediction)]
+                confidence = float(prediction.max()) * 100
+            
+            st.success(f'Prediction: {pred_class.upper()}')
+            st.info(f'Confidence: {confidence:.2f}%')
+            
+            st.write("Class Probabilities:")
+            for i, prob in enumerate(prediction[0]):
+                st.progress(float(prob))
+                st.write(f"{LABEL_CLASS[i]}: {float(prob)*100:.2f}%")
+
+if __name__ == "__main__":
+    main()

requirement.txt

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+pillow==10.4.0
+streamlit==1.39.0
+tensorflow==2.18.0