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

learn = load_learner('export3.pkl')

#catagories = 'apple','barn owl','guacamole','parrot',
catagories = ["white Panthera tigris (White Tiger)", "Panthera tigris (Tiger)", "Acinonyx jubatus (Cheetah)", "Canis familiaris (Dog)", "Canis aureus (Jackal)", "Equus caballus (Horse)", "Equus asinus (Donkey)", "Mister Lincoln (Rose)", "Hibiscus rosa-sinensis (Shoeblackplant)",  "Litchi chinensis (Lichu)",  "Fragaria ananassa (Strawberry)",]
catagories.sort()

def classify_img(img):
    pred_class,pred_idx,probs = learn.predict(img)
    return dict(zip(catagories, map(float,probs)))

image = gr.inputs.Image(shape=(256,256))
label = gr.outputs.Label()
#examples = ['apple.png','owl.png','parrot.png','guacamole.png']

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