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Aspiring Astro
commited on
Commit
·
6426419
1
Parent(s):
4099db1
fix loss and matrix event, remove examples
Browse files
app.ipynb
CHANGED
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@@ -447,7 +447,7 @@
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},
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{
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"cell_type": "code",
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-
"execution_count":
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"id": "a48e7483-c04b-4048-a1ae-34a8c7986a57",
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"metadata": {},
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"outputs": [
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@@ -496,18 +496,27 @@
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"#| export\n",
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"example_images = [ 'cheetah.jpg', 'jaguar.jpg', 'tiger.jpg', 'cougar.jpg', 'lion.jpg', 'african leopard.jpg', 'clouded leopard.jpg', 'snow leopard.jpg', 'hidden.png', 'hidden2.png' ]\n",
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"\n",
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"model_matrix = [ 'models/resnet101-confusion-matrix.png', 'models/resnet18-confusion-matrix.png', 'models/resnet50-confusion-matrix.png',\n",
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"'models/resnet152-confusion-matrix.png', 'models/resnet34-confusion-matrix.png' ]\n",
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"\n",
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"model_losses = [ 'models/resnet101-top-losses.png', 'models/resnet18-top-losses.png', 'models/resnet50-top-losses.png',\n",
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"'models/resnet152-top-losses.png', 'models/resnet34-top-losses.png' ]\n",
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"\n",
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"demo = gr.Blocks()\n",
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"with demo:\n",
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" with gr.Column(variant=\"panel\"):\n",
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@@ -521,13 +530,13 @@
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" losses=gr.outputs.Image(type='filepath', label=\"Top Losses\")\n",
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" result = gr.outputs.Label(label=\"Result\")\n",
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" \n",
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" model.change(fn=select_model, inputs=model, outputs=selected)\n",
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" btnClassify.click(fn=classify_image, inputs=image, outputs=result)\n",
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" img_gallery = gr.Examples(examples=example_images, inputs=image)\n",
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"
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"\n",
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"demo.launch(debug=True, inline=False)\n",
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" # intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )\n",
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@@ -537,15 +546,31 @@
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},
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{
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"cell_type": "code",
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"execution_count":
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"id": "cab071f9-7c3b-4b35-a0d1-3687731ffce5",
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"metadata": {},
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"outputs": [
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"source": [
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"import nbdev\n",
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"nbdev.export.nb_export('app.ipynb', './')\n",
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"print('Export successful')"
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]
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}
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],
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"metadata": {
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "a48e7483-c04b-4048-a1ae-34a8c7986a57",
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"metadata": {},
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"outputs": [
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Keyboard interruption in main thread... closing server.\n"
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]
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"#| export\n",
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"example_images = [ 'cheetah.jpg', 'jaguar.jpg', 'tiger.jpg', 'cougar.jpg', 'lion.jpg', 'african leopard.jpg', 'clouded leopard.jpg', 'snow leopard.jpg', 'hidden.png', 'hidden2.png' ]\n",
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"\n",
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"demo = gr.Blocks()\n",
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"with demo:\n",
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" with gr.Column(variant=\"panel\"):\n",
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" losses=gr.outputs.Image(type='filepath', label=\"Top Losses\")\n",
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" result = gr.outputs.Label(label=\"Result\")\n",
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" \n",
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" btnClassify.click(fn=classify_image, inputs=image, outputs=result)\n",
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" img_gallery = gr.Examples(examples=example_images, inputs=image)\n",
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"\n",
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" # Register all ev\n",
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" model.change(fn=select_model, inputs=model, outputs=selected)\n",
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" model.change(fn=update_matrix, outputs=matrix)\n",
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" model.change(fn=update_losses, outputs=losses)\n",
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"\n",
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"demo.launch(debug=True, inline=False)\n",
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" # intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )\n",
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "cab071f9-7c3b-4b35-a0d1-3687731ffce5",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Export successful\n"
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]
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}
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],
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"source": [
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"import nbdev\n",
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"nbdev.export.nb_export('app.ipynb', './')\n",
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"print('Export successful')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "95f0e7ec-edd2-4afa-a68f-7da8b85b1f61",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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app.py
CHANGED
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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# %% auto 0
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__all__ = ['title', 'description', 'learners', 'models', 'active_name', 'active_model', 'example_images', '
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'
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# %% app.ipynb 1
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from fastai.vision.all import *
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@@ -50,12 +50,6 @@ def update_losses():
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# %% app.ipynb 5
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example_images = [ 'cheetah.jpg', 'jaguar.jpg', 'tiger.jpg', 'cougar.jpg', 'lion.jpg', 'african leopard.jpg', 'clouded leopard.jpg', 'snow leopard.jpg', 'hidden.png', 'hidden2.png' ]
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model_matrix = [ 'models/resnet101-confusion-matrix.png', 'models/resnet18-confusion-matrix.png', 'models/resnet50-confusion-matrix.png',
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'models/resnet152-confusion-matrix.png', 'models/resnet34-confusion-matrix.png' ]
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model_losses = [ 'models/resnet101-top-losses.png', 'models/resnet18-top-losses.png', 'models/resnet50-top-losses.png',
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'models/resnet152-top-losses.png', 'models/resnet34-top-losses.png' ]
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-
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demo = gr.Blocks()
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with demo:
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with gr.Column(variant="panel"):
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losses=gr.outputs.Image(type='filepath', label="Top Losses")
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result = gr.outputs.Label(label="Result")
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model.change(fn=select_model, inputs=model, outputs=selected)
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btnClassify.click(fn=classify_image, inputs=image, outputs=result)
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img_gallery = gr.Examples(examples=example_images, inputs=image)
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demo.launch(debug=True, inline=False)
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# intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )
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# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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# %% auto 0
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__all__ = ['title', 'description', 'learners', 'models', 'active_name', 'active_model', 'example_images', 'demo',
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'classify_image', 'select_model', 'update_matrix', 'update_losses']
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# %% app.ipynb 1
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from fastai.vision.all import *
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# %% app.ipynb 5
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example_images = [ 'cheetah.jpg', 'jaguar.jpg', 'tiger.jpg', 'cougar.jpg', 'lion.jpg', 'african leopard.jpg', 'clouded leopard.jpg', 'snow leopard.jpg', 'hidden.png', 'hidden2.png' ]
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demo = gr.Blocks()
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with demo:
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with gr.Column(variant="panel"):
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losses=gr.outputs.Image(type='filepath', label="Top Losses")
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result = gr.outputs.Label(label="Result")
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btnClassify.click(fn=classify_image, inputs=image, outputs=result)
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img_gallery = gr.Examples(examples=example_images, inputs=image)
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# Register all ev
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model.change(fn=select_model, inputs=model, outputs=selected)
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model.change(fn=update_matrix, outputs=matrix)
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model.change(fn=update_losses, outputs=losses)
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demo.launch(debug=True, inline=False)
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# intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )
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