Add application file

app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: . (unless otherwise specified).
+
+__all__ = ['repo_id', 'learn', 'classify_image', 'categories', 'title', 'description', 'article', 'image', 'label',
+           'examples', 'intf']
+
+# Cell
+import timm
+from fastai.vision.all import *
+import gradio as gr
+
+# Cell
+from huggingface_hub import from_pretrained_fastai
+
+repo_id = "Jimmie/identify-this-insect"
+
+learn = from_pretrained_fastai(repo_id)
+
+# Cell
+categories = learn.dls.vocab
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# Cell
+
+title = "Identify This Insect"
+description = """
+
+This demo was created to distinguish between three types of insects: 'caterpillar', 'centipede', and 'millipede'.
+
+It is just a toy app created mostly because I once got a caterpillar sting and thought that the insect was a centipede and I was scared until I
+googled how different a centipede looks from a caterpillar haha! (The insect that had stung me looked more like the fourth example image below).
+
+Enjoy!
+
+
+"""
+
+article = "Check out how the model was trained: [Training Notebook](https://github.com/jimmiemunyi/deeplearning-experiments/blob/main/notebooks/Centipede_vs_Millipede_vs_Caterpillar.ipynb)."
+image = gr.inputs.Image(shape=(224,224))
+label = gr.outputs.Label()
+examples = ['caterpillar.jpg', 'centipede.jpg', 'millipede.jpg', 'caterpillar-2.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title = title, description = description, article = article)
+intf.launch(inline=False)

requirements.txt

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+fastai==2.7.4
+tim==0.6.5