Hummingbird Classifier

app.py

@@ -0,0 +1,22 @@
+from fastai.vision.all import *
+import gradio as gr
+
+# def is_cat(x): return x[0].isupper()
+
+# Cell
+learn = load_learner('resnet101model.pkl')
+
+# Cell
+categories = ("anna's", 'green-crowned', 'marvelous spatuletail', 'ruby-throated', 'violetear')
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# Cell
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label()
+examples = ['annas.jpeg', 'green-crowned.jpeg', 'marvelous_spatuletail.png', 'ruby-throated.jpeg', 'violetear.jpeg']
+
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

requirements.txt

@@ -0,0 +1 @@
+fastai

resnet101model_2.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a6a03ef2c7bc5db46a61f956695192d278f892ad25768524fd28c1c0c15560b
+size 179208241