app.py

# AUTOGENERATED! DO NOT EDIT! File to edit: load.ipynb.

# %% auto 0
__all__ = ['learn', 'intf', 'classify_image']

# %% load.ipynb 1
import pickle  # or import joblib
from fastai.vision.all import *
import gradio as gr

# %% load.ipynb 3
learn = load_learner('models/archclassifier_v2.pkl')

# %% load.ipynb 6
def classify_image(img):
    img = PILImage.create(img)
    pred_class, pred_idx, probs = learn.predict(img)
    
    # Corrected: Create dict mapping class names to float probabilities
    return dict(zip(learn.dls.vocab, map(float, probs)))

# %% load.ipynb 8
examples = ['examples/1.jpg','examples/2.jpg','examples/3.jpg','examples/4.jpg']

intf = gr.Interface(
    fn=classify_image,
    inputs=gr.Image(),
    outputs=gr.Label(num_top_classes=3),  # show top 3 predictions visually
    examples=examples,
    title="Arch Style Classifier 🏢",
    description="Upload or choose an image to classify the Arch Style."
)

intf.launch()