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

learn = load_learner('export3.pkl')

#catagories = 'apple','barn owl','guacamole','parrot',
catagories = ["white Panthera tigris", "Panthera tigris", "Acinonyx jubatus", "Canis familiaris", "Canis aureus", "Equus caballus", "Equus asinus", "Mister Lincoln", "Hibiscus rosa-sinensis",  "Litchi chinensis",  "Fragaria ananassa",]
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()