#from fastcore.all import * | |
from fastai.vision.all import * | |
from fastbook import load_learner | |
import gradio as gr | |
inf = load_learner('export.pkl') | |
#categories = ('Cat', 'Cheetah', 'Other', 'Leopard', 'Lion', 'Snow Leopard', 'Tiger') | |
def classify_img(img): | |
pred, idx, probs = inf.predict(img) | |
return pred | |
#return dict(zip(categories,map(float,probs))) | |
#|export | |
#This creates the gradio interface | |
image = gr.Image(shape=(192,192)) | |
label = gr.outputs | |
#examples = ['cheetah.jpg','leopard.jpg','img.jpg'] | |
intf = gr.Interface(fn = classify_img, inputs=image,outputs="label") | |
intf.launch() | |