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

#temp = pathlib.PosixPath
#pathlib.PosixPath = pathlib.WindowsPath

learn = load_learner('Bacteria-Classifier.pkl')

categories = ('Acinetobacter.baumanii',
'Actinetobacter.israeli',
'Bacteroides.fragilis',
'Bifidobacterium.spp',
'Candida.albicans',
'Clostridium.perfringens',
'Enterococcus.faecalis',
'Enterococcus.faecium',
'Escherichia.coli',
'Fusobacterium',
'Lactobacillus.casei',
'Lactobacillus.crispatus',
'Lactobacillus.delbrueckii',
'Lactobacillus.gasseri',
'Lactobacillus.jehnsenii',
'Lactobacillus.johnsonii',
'Lactobacillus.paracasei',
'Lactobacillus.plantarum',
'Lactobacillus.reuteri',
'Lactobacillus.rhamnosus',
'Lactobacillus.salivarius',
'Listeria.monocytogenes',
'Micrococcus.spp',
'Neisseria.gonorrhoeae',
'Porfyromonas.gingivalis',
'Propionibacterium.acnes',
'Proteus',
'Pseudomonas.aeruginosa',
'Staphylococcus.aureus',
'Staphylococcus.epidermidis',
'Staphylococcus.saprophiticus',
'Streptococcus.agalactiae',
'Veionella')

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

image = gr.Image(shape=(244,244))
label = gr.Label()
examples = ['Fusobacterium_sample.png','Veionella_sample.png','Clostridium.perfringens_sample.png']

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