Add examples and explanation

app.py

@@ -1,16 +1,44 @@
 from fastai.vision.all import *
 import gradio as gr
 
+
 def greet(name):
     return "Hello " + name + "!!"
 
 
-learn = load_learner('model-v7.pkl')
+learn = load_learner("model-v7.pkl")
 
 labels = learn.dls.vocab
+
+
 def predict(img):
     img = PILImage.create(img)
-    pred,pred_idx,probs = learn.predict(img)
+    pred, pred_idx, probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)), outputs=gr.outputs.Label(num_top_classes=3)).launch(share=True)
+
+examples = [
+    "a2_b_m.jpg",
+    "a2_coeur_lyon.jpg",
+    "gzup_america.jpg",
+    "gzup_gameboy.jpg",
+    "pa_425.jpg",
+    "pa_1341.jpg",
+    "stork_music.jpg",
+    "stork_prince.jpg",
+]
+
+DESCRIPTION = """
+Street art deep learning model. It's trained to recognize the style of the following artists active in Paris:
+[A2](https://a2-streetart.com/), [gzup](https://www.gzup.fr/in-the-streets/), [invader](https://www.instagram.com/invaderwashere), [stork](https://www.instagram.com/stork_pixelart/).
+For more AI experiments check out my [newsletter](https://newsletter.pnote.eu) 💫.
+"""
+
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=3),
+    examples=examples,
+    title="Art reco, recognizer of street art",
+    description=DESCRIPTION
+).launch(share=True)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:630e9cc5c5ce038ccdf0a9b7a770b1eb849ab81a4a14e7102cb9a6ee06dcc54f
+size 46968626