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# -*- coding: utf-8 -*-
"""app.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1vlBRU28F38BKH1XkEkhTGHIb4Si-o1Dt
"""
# -*- coding: utf-8 -*-
"""Untitled42.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1E2wzzc6nLLxlKiOSWLuRYe2ormOLQcuN
"""
__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
# Cell
from fastai.vision.all import *
import gradio as gr
import timm
# Cell
learn = load_learner('model.pkl')
# Cell
categories = learn.dls.vocab
def classify_image(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float,probs)))
# Cell
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ['beefsteak.jpeg','cherry.jpeg','grape.jpeg','green.jpeg','heirloom.jpeg', 'kumato.jpeg','roma.jpeg']
# Cell
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch() |