| import streamlit as st |
| import tensorflow as tf |
| import numpy as np |
| import pickle |
| from tensorflow.keras.preprocessing import image |
|
|
| model = tf.keras.models.load_model("animal_mobilenet_model.keras") |
|
|
| labels = pickle.load(open("labels.pkl","rb")) |
|
|
| class_names = list(labels.keys()) |
|
|
| st.title("🐾 Animal Classifier (MobileNetV2)") |
|
|
| uploaded_file = st.file_uploader("Upload Animal Image") |
|
|
| if uploaded_file: |
|
|
| img = image.load_img(uploaded_file, target_size=(224,224)) |
|
|
| img_array = image.img_to_array(img)/255 |
|
|
| img_array = np.expand_dims(img_array, axis=0) |
|
|
| prediction = model.predict(img_array) |
|
|
| predicted_class = class_names[np.argmax(prediction)] |
|
|
| st.success(f"Predicted Animal: {predicted_class}") |
