_all__ = ['Superficial spreading melanoma','Nodular melanoma','Lentigo maligna melanoma', 'Acral lentiginous melanoma','Desmoplastic melanoma']

# Cell
from fastai.vision.all import *
import gradio as gr

# Cell
learn = load_learner('model.pkl')

# Cell
categories = learn.dls.vocab

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

# Cell
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()

examples = ['desmoplastic.jpeg', 'lentigo melanoma.jpg','acral.jpeg', 'malignant melanoma.jpg', 'melanoma.jpeg', 'nodular melanoma.jpeg','Superficial Spreading Melanoma.jpeg']

# Cell
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()