let's deploy to huggingface spaces

app.py

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+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
+
+# %% auto 0
+__all__ = ['single_classifier', 'multi_class_classifier', 'multi_label_classifier', 'binary_labels', 'multi_class_labels',
+           'multi_label_labels', 'label_func', 'single_classification', 'multi_class_classification',
+           'multi_label_classification']
+
+# %% app.ipynb 1
+import gradio as gr
+import nbdev
+from fastai.vision.all import *
+import os
+
+# %% app.ipynb 2
+def label_func(f): return 'Cat' if f[0].isupper() else 'Dog'
+
+# %% app.ipynb 3
+single_classifier       = load_learner('models/dog-cat-classifier.pkl')
+multi_class_classifier  = load_learner('models/breeds-classifier.pkl')
+multi_label_classifier  = load_learner('models/multi-label-classification.pkl')
+
+# %% app.ipynb 4
+binary_labels = single_classifier.dls.vocab
+
+def single_classification(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = single_classifier.predict(img)
+    return dict(zip(binary_labels, map(float, probs)))
+
+# %% app.ipynb 5
+multi_class_labels = multi_class_classifier.dls.vocab
+
+def multi_class_classification(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = multi_class_classifier.predict(img)
+    return dict(zip(multi_class_labels, map(float, probs)))
+
+# %% app.ipynb 6
+multi_label_labels = multi_label_classifier.dls.vocab
+
+def multi_label_classification(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = multi_label_classifier.predict(img)
+    return dict(zip(multi_label_labels, map(float, probs)))
+
+# %% app.ipynb 7
+with gr.Blocks() as demo:
+    gr.Markdown("This demo allowing you to try different vision classification models - \
+    From binary classification through multi-class and multi-label classification and finally segmentation.")
+
+    with gr.Tab("Binary"):
+        with gr.Row():
+            with gr.Column():
+                b_image_input = gr.inputs.Image(shape = (460,460))
+                with gr.Row():
+                    b_button = gr.Button("Run")
+
+                b_examples = 'models/Examples/Pets'
+                examples = gr.Examples(examples=[b_examples + '/shiba_inu_44.jpg', b_examples + '/Bengal_132.jpg',], inputs = b_image_input)
+            binary_out = gr.Label(num_top_classes=len(binary_labels))
+        
+        
+    with gr.Tab("MultiClass"):
+        with gr.Row():
+            with gr.Column():
+                m_image_input = gr.inputs.Image(shape = (460,460))
+                with gr.Row():
+                    m_button = gr.Button("Run")
+
+                m_examples = 'models/Examples/Pets'
+                examples = gr.Examples(examples=[os.path.join(m_examples, s) for s in os.listdir(m_examples) if s.endswith('jpg')], inputs = m_image_input)
+            multi_out = gr.Label(num_top_classes=len(multi_class_labels))
+        
+
+    with gr.Tab("MultiLabel"):
+        with gr.Row():
+            with gr.Column():
+                ml_image_input = gr.inputs.Image(shape = (460,460))
+                with gr.Row():
+                    ml_button = gr.Button("Run")
+                
+                ml_examples = 'models/Examples/Pascal'
+                examples = gr.Examples(examples=[os.path.join(ml_examples, s) for s in os.listdir(ml_examples) if s.endswith('jpg')], inputs = ml_image_input)
+    
+            multil_out = gr.Label(num_top_classes=len(multi_label_labels))
+        
+    b_button.click(single_classification, inputs=b_image_input, outputs=binary_out)
+    m_button.click(multi_class_classification, inputs=m_image_input, outputs=multi_out)
+    ml_button.click(multi_label_classification, inputs=ml_image_input, outputs=multil_out)
+
+demo.launch()

models/Examples/Pascal/000751.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pascal/002009.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pascal/003800.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pascal/008964.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/Bengal_132.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/Birman_198.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/Bombay_86.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/Ragdoll_154.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/Russian_Blue_36.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/beagle_82.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/Examples/Pets/shiba_inu_44.jpg:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://51dw3zi9gvg-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/breeds-classifier.pkl

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+oid sha256:e6e9b3904274b6dc38aa4c324690299f418f5c9fef7b9248f1274f3a541b2270
+size 87639765

models/breeds-classifier.pkl:Zone.Identifier

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+ZoneId=3
+HostUrl=https://3vx4kj165xn-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/dog-cat-classifier.pkl

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+oid sha256:f7a50dd19768eceee64045a07a3a7ac969613fd71574c9655f3f6d74c1e4d06f
+size 87560565

models/dog-cat-classifier.pkl:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://3vx4kj165xn-496ff2e9c6d22116-0-colab.googleusercontent.com/

models/multi-label-classification.pkl

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+oid sha256:96672632a8accfb60848663ad83ccb852e6bd7fe363d5a7aea6160da8381836b
+size 87572123

models/multi-label-classification.pkl:Zone.Identifier

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+[ZoneTransfer]
+ZoneId=3
+HostUrl=https://3vx4kj165xn-496ff2e9c6d22116-0-colab.googleusercontent.com/

requirements.txt

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+fastai