app.py

import gradio as gr
import os
from core.predict import ImageClassifier
from PIL import Image

cwd = os.getcwd()
model_path = os.path.join(cwd, "model", "cnn_model.pth")
class_name = {0: 'Cat', 1: 'Dog', 2: 'Person'}
classifier = ImageClassifier(model_path=model_path, class_name=class_name)

def predict(image):
    image_path = "uploaded_image.jpg"
    image.save(image_path)
    label, output_image_path = classifier.predict(image_path)
    return label, Image.open(output_image_path)
    
    
demo = gr.Interface(
    fn = predict,
    inputs = gr.Image(type="pil"),
    outputs = [gr.Textbox(label="Predicted Class"), gr.Image(label="Labeled Image")],
    title="Image Classification Gradio App",
    description="Upload an image to classify it as Dog, Cat or Person."
)

if __name__ == "__main__":
    demo.launch()