Add model, interface, and example

app.py

@@ -0,0 +1,36 @@
+from fastai.learner import load_learner
+from fastai.vision.core import PILImage
+import gradio as gr
+
+learn = load_learner('export.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    preds, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Turtle Pleasure"
+description = 'An image classifier for recognizing turtle species, created using <a href="fast.ai">FastAI</a>.'
+article = """
+<p>The model is a pre-trained ResNet18 fine-tuned on a dataset obtained from
+<a href="https://www.inaturalist.org">iNaturalist</a> and <a href="https://www.gbif.org/">GBIF</a>.
+It recognizes the following species (according to GBIF, the 50 most observed turtles in North America):</p>
+
+<ul><li>""" + "</li><li>".join(labels) + """</li></ul>
+
+<h3>References:</h3>
+<p>GBIF.org (8 September 2023) GBIF Occurrence Download <a href="https://doi.org/10.15468/dl.mvss9v">"https://doi.org/10.15468/dl.mvss9v"</a></p>
+"""
+
+iface = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(shape=(400, 400)), 
+    outputs=gr.Label(num_top_classes=3),
+    title=title,
+    description=description,
+    article=article,
+    examples=['test_snapper.jpg']
+)
+iface.launch()
+

export.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:02fe4aaa0034ef4e345e9791a52fa6fe5fa24fb044610b4805a26f90adef38f8
+size 50040813