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import gradio as gr
from fastai.vision.all import *
# Define a function for determining if image is a cat
def is_cat(x):
return x[0].isupper()
# Load pretrained model
learn = load_learner("model.pkl")
categories = ("Dog", "Cat")
def classify_image(img):
"""
Classify an image as a dog or cat.
:param img: Image to classify
:return: Dictionary of probabilities for each class
"""
pred, pred_idx, probs = learn.predict(img)
return dict(zip(categories, map(float, probs)))
image = gr.inputs.Image(shape=(224, 224))
label = gr.outputs.Label()
examples = ["dog.jpg", "cat.jpg", "tiger.jpg", "wolf.jpg"]
intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
intf.launch()
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