from fastai.vision.all import *
import gradio as gr
import pathlib
import fastai.learner

def custom_load_learner(fname, cpu=True, pickle_module=pickle):
    """Load a Learner from file in `fname` and ensure it's using a platform-independent path."""
    map_loc = None if torch.cuda.is_available() and not cpu else 'cpu'
    try:
        res = torch.load(fname, map_location=map_loc, pickle_module=pickle_module)
    except ModuleNotFoundError as e:
        raise ImportError(f"{e}. To load the model on a different device, you may need to install the fastai library.")
    
    if 'WindowsPath' in str(type(res.path)):
        res.path = pathlib.Path(res.path)
        
    return res

def is_cat(x): return x[0].isupper()

learn = custom_load_learner('model.pkl')

categories = ('dog', 'cat')

def classify_image(img):
    pred, idx, probs = learn.predict(img)
    return dict(zip(categories, map(float, probs)))

image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
exemple = ["dog.jpg", "cat.jpg"]

intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=exemple)
intf.launch(inline=False)