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from fast.ai.vision.all import * | |
import gradio as gr | |
# def greet(name): | |
# return "Hello " + name + "!!" | |
# iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
# iface.launch() | |
# from: | |
# https://course.fast.ai/Lessons/lesson2.html | |
# https://github.com/fastai/fastbook/blob/master/02_production.ipynb | |
#learn_inf = load_learner(path/'export.pkl') | |
#learn_inf.predict('images/grizzly.jpg') | |
#learn_inf.dls.vocab | |
# model created from: https://www.kaggle.com/code/zachwormgoor/stock-photo-recognizer | |
learn = load_learner('model.pkl') | |
categories = ('stock', 'amateur') | |
def classify(img): | |
pred,idx,probs = learn.predict(img) | |
return dict(zip(categories, map(float,probs))) | |
image = gr.inputs.Image(shape=(192, 192)) | |
label = gr.outputs.Label() | |
examples = ['stock.jpg', 'amateur.jpg', 'unsure.jpg'] | |
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
intf.launch(inline=False) |