added example images

app.py

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+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('petClassifierModel.pkl')
+
+
+categories = learn.dls.vocab
+
+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 = ['basset_hound2.jpg','Boxer.jpg','cocker_spaniel.jpg','Keeshond.jpg','Siamese.jpg', 'sphynx.jpg', 'St_Bernard_Dog.jpg']
+
+iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+iface.launch()

requirements.txt

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+pytorch
+fastai
+gradio
+pandas
+numpy