from fastai.vision.all import *
from fastai.vision.core import PILImage
import gradio as gr


# register your custom fn
def is_cat(x): return x[0].isupper()


# make sure it's in __main__ so load_learner can find it
import __main__

__main__.is_cat = is_cat

learn = load_learner('models/model.pkl')
categories = ('Dog', 'Cat')


def classify_image(img):
    img = PILImage.create(img)  # ← convert here
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))


image = gr.Image(type="pil")  # or type="numpy" for Option B
label = gr.Label(num_top_classes=2)
examples = ['dog.png', 'cat.png', 'dunno.png']

intf = gr.Interface(classify_image, image, label, examples=examples)
intf.launch(share=False)