import gradio as gr
from fastai.vision.all import *
import skimage

training_set = "mane6-8000"


# this is here, because it needs to be, otherwise I have no friggin clue
def get_x(r): return os.path.join(training_set, r['fname'].replace('png', 'jpg').replace('gif', 'jpg').replace('svg', 'jpg')) # the replacing part is an interim solution lol (bug on a different end)
def get_y(r): return r['tag']

learn = load_learner('export.pkl') # pls rename

labels = learn.dls.vocab
def predict(img):
    img = PILImage.create(img)
    pred,pred_idx,probs = learn.predict(img)
    return {labels[i]: float(probs[i]) for i in range(len(labels))}

title = "Ember"
description = ""
examples = ["examples/1.jpg", "examples/2.jpg", "examples/3.jpg", "examples/4.jpg"]
interpretation='default'
enable_queue=True

gr.Interface(
    fn=predict,
    inputs=gr.inputs.Image(shape=(400, 400)),
    outputs=gr.outputs.Label(num_top_classes=3),
    title=title,
    description=description,
    examples=examples,
    interpretation=interpretation,
    enable_queue=enable_queue).launch()

"""
LINKS
https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial
"""