trial-minima / app.py
Laks Srini
Update to be classifier
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
# %% auto 0
__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_img']
# %% app.ipynb 1
from fastai.vision.all import *
import gradio as gr
# def is_cat(x): return x[0].isupper()
# %% app.ipynb 3
learn = load_learner("model.pkl")
# %% app.ipynb 5
categories = ['Bathroom', 'Bedroom', 'Floor plan', 'Front', 'Kitchen', 'Living room', 'Parking', 'Porch', 'Swimming pool', 'Views', 'Yard']
def classify_img(img):
pred,idx,probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
# %% app.ipynb 7
image = gr.inputs.Image(shape=(192, 192))
label = gr.outputs.Label()
examples = ["kitchen.jpg", "living_room.jpg", "living_room2.jpg"]
intf = gr.Interface(fn=classify_img, inputs=image, outputs=label, examples=examples)
intf.launch(inline=False)