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.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
+forest.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,31 @@
+from fastai.vision.all import *  # noqa: F403
+from fastai.vision.widgets import *  # noqa: F403
+import gradio as gr
+
+# Load the pre-trained model, the model has been trained on the following Butterflies:
+# 1. Monarch
+# 2. Painted Lady
+# 3. Red Admiral
+# 4. Viceroy
+# 5. Bronze Copper
+# 6. Buckeye
+# The model has an error_rate of ~6.7%
+learn = load_learner('kinds_of_butterflies_model.pkl')
+
+
+def classify_image(img):
+  pred, idx, probs = learn.predict(img)
+  categories = learn.dls.vocab
+  label_pred = widgets.Label()
+  label_pred.value = f'Prediction: {pred}; Probability: {probs[idx]:.04f}'
+  print(label_pred)
+  float_values = map(float, probs)
+  return dict(zip(categories, float_values))
+
+
+image = gr.Image()
+label = gr.Label()
+examples = ['forest.jpg', 'monarch.jpg', 'swallow.jpg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

kinds_of_butterflies_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c25217ab76258493ee5f2ec585568f924a0d055ce532d392d8babeb9bb46f78c
+size 46980542