app.py

import json
import numpy as np
import tensorflow as tf
from PIL import Image
import gradio as gr

# Load model
model = tf.keras.models.load_model("animal_cnn.keras")

# Load class names
with open("class_names.json", "r") as f:
    class_names = json.load(f)

# Preprocess function
def preprocess_image(image):
    image = image.resize((224, 224))
    image = np.array(image) / 255.0
    image = np.expand_dims(image, axis=0)
    return image

# Prediction function
def predict(image):
    image = preprocess_image(image)
    predictions = model.predict(image)[0]

    top_index = np.argmax(predictions)
    confidence = float(predictions[top_index])

    return f"{class_names[top_index]} ({confidence*100:.2f}%)"

# Gradio UI
interface = gr.Interface(
    fn=predict,
    inputs=gr.Image(type="pil"),
    outputs="text",
    title="🐾 Animal Classifier",
    description="Upload an image to detect the animal"
)

interface.launch()