Create app.py

app.py

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+import streamlit as st
+import numpy as np
+import tensorflow as tf
+import tensorflow_hub as hub
+import cv2
+from PIL import Image
+import time
+
+# Set page title and favicon
+st.set_page_config(page_title="Cat and Dog Classifier", page_icon="🐱🐶")
+
+# Load the pre-trained model
+mobilenet_model = 'https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4'
+pretrained_model = hub.KerasLayer(mobilenet_model, input_shape=(224, 224, 3), trainable=False)
+num_of_classes = 2
+model = tf.keras.Sequential([
+    pretrained_model,
+    tf.keras.layers.Dense(num_of_classes)
+])
+
+model.compile(
+    optimizer='adam',
+    loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
+    metrics=['acc']
+)
+
+model.load_weights("cat_dog_classifier.h5")
+
+# Define functions for image resizing and classification
+def preprocess_image(image):
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    image = cv2.resize(image, (224, 224))
+    image = image / 255.0
+    image = np.expand_dims(image, axis=0)
+    return image
+
+def classify_image(image):
+    image = preprocess_image(image)
+    prediction = model.predict(image)
+    return np.argmax(prediction)
+
+# Sidebar
+st.sidebar.header("Cat and Dog Classifier")
+uploaded_image = st.sidebar.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+
+# Main content
+st.title("Cat/Dog Image Classification")
+
+if uploaded_image:
+    with st.spinner("Uploading image..."):
+        time.sleep(2)  # Simulate image upload process, replace with actual image upload logic
+
+    st.success("Image upload complete!")
+
+    image = Image.open(uploaded_image)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+    if st.button("Classify"):
+        image = np.array(image)
+        pred_label = classify_image(image)
+
+        if pred_label == 0:
+            st.write('<div style="font-size: 24px; color: white;">Prediction: It\'s a Cat 😺</div>', unsafe_allow_html=True)
+        else:
+            st.write('<div style="font-size: 24px; color: white;">Prediction: It\'s a Dog 🐶</div>', unsafe_allow_html=True)
+
+# Add a footer with CSS for positioning
+st.markdown(
+    """
+    <div style="position: fixed; bottom: 0; right: 10px; padding: 10px; color: white;">
+        <a href="https://github.com/sg-sparsh-goyal" target="_blank" style="color: white; text-decoration: none;">
+            ✨ Github
+        </a><br>
+        By Sparsh
+    </div>
+    """,
+    unsafe_allow_html=True
+)