create app.py

app.py

@@ -0,0 +1,47 @@
+from fastai.vision.all import load_learner
+import gradio as gr 
+
+chicken_breeds = [
+ 'Austra White',
+ 'Black Sex Link',
+ 'Blue Laced Red Wyandotte',
+ 'Bresse',
+ 'Cherry Egger',
+ 'Cochin',
+ 'Cornish Cross',
+ 'Cream Legbar',
+ 'Easter Egger',
+ 'Frizzle',
+ 'Iowa Blue',
+ 'Jersey Giant',
+ 'Nankin',
+ 'New Hampshire',
+ 'Orpingtons',
+ 'Polish',
+ 'Shamo',
+ 'Silkie',
+ 'Silver Laced Wyandotte',
+ 'Turken (Naked Neck)'
+]
+
+version = 2
+model_path = f"chicken_breed_recognizer-v{version}.pkl"
+model = load_learner(model_path)
+
+def recognize_image(image):
+    pred, idx, probs = model.predict(image)
+    return dict(zip(cap_labels, map(float, probs)))
+
+image = gr.inputs.Image(shape=(192, 192))
+label = gr.outputs.Label()
+
+examples = [
+  'test_images/test_00.jpg',
+  'test_images/cornish_cross_test_01.jpg'
+  'test_images/frizzle_test_03.jpg',
+  'test_images/polish_test_05.jpg',
+  'test_images/blue_laced_red_wyandotte_09.jpg'
+]
+
+iface = gr.Interface(fn=recognize_image, inputs=image, outputs=label, examples=examples)
+iface.launch(inline=False)