yangtommy6/Computer_Vision_Project

1from fastai.vision.all import *2import gradio as gr 3 4learn = load_learner('model.pkl')5 6categories = ('A room', 'Albatross', 'Anaconda', 'Bears', 'Bison', 'Bobcat', 'Buffalo', 'Cheetah', 'Cobra', 'Crocodile', 'Crowd', 'Dingo', 'Elephant', 'Eurasian Lynx', 'Field', 'Gorilla', 'Kangaroo', 'Koala', 'Komodo Dragon', 'Leopard', 'Lion' , 'Llama', 'Manatee', 'Monkey','Moose','Natural river', 'Organgutan', 'Panda', 'Penguins', 'Platypus', 'Reindeer', 'Rhinoceros', 'Robot', 'Seals', 'Tasmanian Devil','Technology products', 'Tigar', 'Wolf', 'anime', 'automobile', 'bird', 'book', 'building', 'capybara', 'cat', 'cave', 'city', 'computer', 'deep sea creatures', 'dessert', 'dog', 'dophin', 'fish', 'flag', 'food', 'forest', 'game', 'gas station', 'hamster', 'icon', 'jaguar', 'jellyfish', 'kitchen', 'lake', 'lantern', 'man', 'mountain', 'phone', 'rabbit','sea','shark', 'sky', 'sloth', 'snow', 'turtle', 'universe', 'whale', 'women')7def classify_image(img):8  pred,idx,probs = learn.predict(img)9  return dict(zip(categories, map(float,probs)))10 11image = gr.inputs.Image(shape=(192,192))12label = gr.outputs.Label()13intf = gr.Interface(fn = classify_image, inputs = image, outputs = label)14intf.launch(inline = False)