OK

.gitattributes

@@ -6,6 +6,7 @@
 *.gz filter=lfs diff=lfs merge=lfs -text
 *.h5 filter=lfs diff=lfs merge=lfs -text
 *.joblib filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
 *.lfs.* filter=lfs diff=lfs merge=lfs -text
 *.model filter=lfs diff=lfs merge=lfs -text
 *.msgpack filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -1 +1,3 @@
 .idea
+.ipynb_checkpoints
+.DS_Store

README.md

@@ -11,3 +11,23 @@ license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+# Train and download the model
+
+The notebook that generated the model pickle file `model.pkl` is 
+[here](https://www.kaggle.com/code/cfahed/saving-a-basic-fastai-model/edit).
+
+# Setup a fully working Fastai environment on Mac
+
+Install [Mamba](https://mamba.readthedocs.io/en/latest/installation.html) which is a faster Conda.
+And both are preferred to _pip_ because _pip_ doesn't install GPU dependencies.
+
+Then, run the following commands:
+
+    mamba init
+    mamba install -c fastchan fastai
+    mamba install -c fastai nbdev
+    mamba install jupyter
+    pip install gradio
+
+Finally, launch Jupyter with `jupyter notebook`.

app.py

@@ -1,7 +1,28 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../dogsvscats.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
+
+# %% ../dogsvscats.ipynb 2
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+def is_cat(x): return x[0].isupper()
+
+# %% ../dogsvscats.ipynb 4
+learn = load_learner('model.pkl')
+
+# %% ../dogsvscats.ipynb 13
+categories = ('Dog', 'Cat')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))
+
+# %% ../dogsvscats.ipynb 15
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+examples = ['dog.jpg', 'cat.jpg']
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0220c047d5d29a0a69fc681fd7ed4ad025f3eb8e95dd515a5628529981237c83
+size 47061355