app.py

import gradio as gr
from fastai.vision.all import load_learner, PILImage
import os
import pathlib

if os.name == "nt":  # Windows
    pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner("cards_classification.pkl", cpu=True)

def classify_image(image):
    if image is None:
        return {}
    img = PILImage.create(image)
    pred_class, pred_idx, probs = learn.predict(img)
    return {learn.dls.vocab[i]: float(probs[i]) for i in range(len(probs))}

# Create the interface
with gr.Blocks() as iface:
    gr.Markdown(
        """
        # 🃏 Playing Card Image Classifier
        
        This AI model can recognize and classify images of standard playing cards using deep learning.
        
        ### How it works:
        Upload an image of a playing card, and the model will predict which card it is from a full deck of cards.
        
        ### Supported Cards:
        The model can identify **all standard playing cards**, including:
        - Aces, numbers (2–10), Jacks, Queens, and Kings
        - All four suits: Clubs, Diamonds, Hearts, and Spades
        - Joker card (In total: 53 classes)
        
        ### Tips for best results:
        - Make sure the card is fully visible
        - Avoid heavy glare, blur, or occlusion
        - One card per image works best
        """
    )
    
    with gr.Row():
        with gr.Column():
            input_image = gr.Image(type="pil", label="Upload Card Image")
            submit_btn = gr.Button("🔍 Identify Card", variant="primary")
        with gr.Column():
            output_label = gr.Label(num_top_classes=3, label="Predictions")
    
    gr.Examples(
        examples=[
            ["test_images/king_of_diamonds.jpg"],
            ["test_images/jack_of_spades.jpg"],
            ["test_images/ace_of_diamonds.jpg"],
            ["test_images/three_of_hearts.jpg"],
            ["test_images/ace_of_spades.jpg"]
        ],
        inputs=input_image,
        label="Try an example"
    )
    
    submit_btn.click(fn=classify_image, inputs=input_image, outputs=output_label)

if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)