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from fastai.vision.all import * | |
import gradio as gr | |
from enum import Enum | |
class Phase(Enum): | |
FIRST_QUARTER = "First Quarter" | |
FULL_MOON = "Full Moon" | |
NEW_MOON = "New Moon" | |
THIRD_QUARTER = "Thrid Quarter" | |
WANING_CRESCENT = "Waning Crescent" | |
WANING_GIBBOUS = "Waning Gibbous" | |
WAXING_CRESCENT = "Waxing Crescent" | |
WAXING_GIBBOUS = "Waxing Gibbous" | |
#import model | |
learn = load_learner('moon_v1.pkl') | |
#create gradio interface | |
def classify_image(image): | |
pred, idx, probs = learn.predict(image) | |
return dict(zip(Phase._value2member_map_, map(float, probs))) | |
#define the inputs and ouputs for the gradio interface | |
image = gr.inputs.Image(shape=(192, 192)) | |
label = gr.outputs.Label() | |
examples = ['moon1.jpg', 'moon2.jpg', 'moon3.jpg'] | |
#What function do you call to get the output | |
intf = gr.Interface(fn=classify_image, inputs= image, outputs=label, examples=examples) | |
intf.launch() |