#import gradio as gr | |
# def greet(name): | |
# return "Hello " + name + "!!" | |
# iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
# iface.launch() | |
from fastai.vision.all import * | |
import gradio as gr | |
def is_cat(x): return x[0].isupper() | |
learn = load_learner('model.pkl') | |
categories = ('Dog', 'Cat') | |
def classify_image(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 = ['cat.jpg'] | |
#intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples) | |
intf = gr.Interface(fn=classify_image, | |
inputs=gr.Image(type="pil"), | |
outputs=gr.Label(num_top_classes=3), | |
examples=["cat.jpg"]) | |
intf.launch(inline=False) | |