Add model notebook and app.py

.gitignore

@@ -0,0 +1,2 @@
+.ipynb_checkpoints/
+trees/

.python-version

@@ -1 +0,0 @@
-3.9

app.py

@@ -1,7 +1,20 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'classify_image']
+
+# %% app.ipynb 2
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# %% app.ipynb 3
+learn = load_learner('model.pkl')
+
+# %% app.ipynb 7
+# NOTE: Put in alphabetical order
+categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+def classify_image(img):
+  pred, idx, probs = learn.predict(img)
+  # Change each probability to a float, since Gradio doesn't support Tensors or NumPy
+  return dict(zip(categories, map(float, probs)))

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f040356bc64b3b08d0804b78d6e662e55225f73073ec7a5506dc8192bf9f8bba
+size 46964477

requirements.txt

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+fastai
+scikit-image