first push of bird identifier

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import skimage
+import timm
+
+
+# quick function to strip the leading ###. off the parent label name
+def strip_parent_num(o):
+  return parent_label(o).split('.')[1]
+
+# load the model
+learn = load_learner('birds-convnext_small_in22k.pkl')
+
+#function to run the image through the model and get the prediction
+labels = learn.dls.vocab
+def predict(img):
+    img = PILImage.create(img)
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+# Gradio customizations
+title =  'Bird Identifier'
+description = 'This model will predict the type of bird from an image.\n\nThe convnext_tiny_in22k model was refined using the CUB_200_2011 bird dataset.'
+examples = ['cardinal1.jpeg', 'crow.jpg']
+interpretation = 'default'
+enable_queue = True
+article = '''<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Learning from -> Gradio + HuggingFace Spaces: A Tutorial</a></p>'''
+
+# Deploy gradio
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch(share=True)
+

birds-convnext_small_in22k.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:4834a280d712f1009acce525e620a25c9dc347b2fbb67926d475328e2e01e27d
+size 201854910

requirements.txt

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+fastai
+scikit-image
+timm