init

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,18 @@
+from fastai.vision.all import *
+import gradio as gr
+
+learn = load_learner('export.pkl')
+labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    preds,preds_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = 'Horse vs Donkey Classifier'
+description = 'A Horse versus Donkey classifier trained on using DuckDuckGo search engine. Created a demo as part of fastai course'
+
+examples = [Path('examples')/'donkey.jpg', Path('examples')/'horse.jpg', Path('examples')/'animated_horse.jpg', Path('examples')/'animated_donkey.jpg', Path('examples')/'hybrid.jpg']
+
+iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(type='pil', shape=(224, 224)), title=title, description=description, outputs=gr.outputs.Label(num_top_classes=2), examples=examples, enable_queue=True)
+iface.launch()

export.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e8a465536322958668b64368dbea1af06f89a1ad671fe31ce2c5daa83e9753d3
+size 102891209