Brian Sigafoos commited on
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1 Parent(s): 9dc272e

Add title and link to blog post

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Files changed (3) hide show
  1. README.md +1 -1
  2. app.ipynb +10 -5
  3. app.py +12 -7
README.md CHANGED
@@ -2,7 +2,7 @@
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  title: Fastai Trees
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  emoji: πŸ‚
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  colorFrom: green
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- colorTo: brown
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  sdk: gradio
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  sdk_version: 3.14.0
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  app_file: app.py
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  title: Fastai Trees
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  emoji: πŸ‚
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  colorFrom: green
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+ colorTo: yellow
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  sdk: gradio
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  sdk_version: 3.14.0
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  app_file: app.py
app.ipynb CHANGED
@@ -79,7 +79,6 @@
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  "\n",
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  "categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')\n",
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  "\n",
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- "\n",
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  "def classify_image(img):\n",
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  " pred, idx, probs = learn.predict(img)\n",
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  " # Change each probability to a float, since Gradio doesn't support Tensors or NumPy\n",
@@ -109,15 +108,21 @@
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  "metadata": {},
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  "outputs": [],
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  "source": [
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- "#|export\n",
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  "image = gr.inputs.Image(shape=(192, 192))\n",
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  "label = gr.outputs.Label()\n",
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  "examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',\n",
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  " 'images/silver_maple.jpg', 'images/willow_oak.jpg']\n",
 
 
 
 
 
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  "\n",
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- "interface = gr.Interface(fn=classify_image, inputs=image,\n",
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- " outputs=label, examples=examples)\n",
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- "interface.launch(inline=False)"
 
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  ]
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  },
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  {
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  "\n",
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  "categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')\n",
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  "\n",
 
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  "def classify_image(img):\n",
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  " pred, idx, probs = learn.predict(img)\n",
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  " # Change each probability to a float, since Gradio doesn't support Tensors or NumPy\n",
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  "metadata": {},
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  "outputs": [],
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  "source": [
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+ "# |export\n",
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  "image = gr.inputs.Image(shape=(192, 192))\n",
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  "label = gr.outputs.Label()\n",
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  "examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',\n",
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  " 'images/silver_maple.jpg', 'images/willow_oak.jpg']\n",
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+ "# More useful args\n",
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+ "title = \"Tree leaf classifier demo\"\n",
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+ "description = \"A tree leaf classifier demo, trained on images downloaded from DuckDuckGo. Created as a demo of HuggingFace Spaces and Gradio.\"\n",
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+ "article = \"<p>From this blog post: <a href='https://briansigafoos.com/ml-quick-start' target='_blank'>Machine Learning quick start by Brian Sigafoos</a></p>\"\n",
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+ "interpretation = 'default'\n",
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  "\n",
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+ "interface = gr.Interface(fn=classify_image, inputs=image, outputs=label,\n",
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+ " examples=examples, title=title, description=description,\n",
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+ " article=article, interpretation=interpretation)\n",
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+ "interface.launch(inline=False)\n"
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  ]
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  },
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  {
app.py CHANGED
@@ -1,8 +1,8 @@
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  # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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  # %% auto 0
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- __all__ = ['learn', 'categories', 'image', 'label',
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- 'examples', 'interface', 'classify_image']
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  # %% app.ipynb 2
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  from fastai.vision.all import *
@@ -14,19 +14,24 @@ learn = load_learner('model.pkl')
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  # %% app.ipynb 7
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  categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')
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-
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  def classify_image(img):
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  pred, idx, probs = learn.predict(img)
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  # Change each probability to a float, since Gradio doesn't support Tensors or NumPy
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  return dict(zip(categories, map(float, probs)))
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-
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  # %% app.ipynb 10
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  image = gr.inputs.Image(shape=(192, 192))
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  label = gr.outputs.Label()
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  examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',
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  'images/silver_maple.jpg', 'images/willow_oak.jpg']
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-
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- interface = gr.Interface(fn=classify_image, inputs=image,
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- outputs=label, examples=examples)
 
 
 
 
 
 
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  interface.launch(inline=False)
 
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  # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
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  # %% auto 0
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+ __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'title', 'description', 'article', 'interpretation', 'interface',
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+ 'classify_image']
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  # %% app.ipynb 2
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  from fastai.vision.all import *
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  # %% app.ipynb 7
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  categories = ('ash', 'chestnut', 'ginkgo biloba', 'silver maple', 'willow oak')
16
 
 
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  def classify_image(img):
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  pred, idx, probs = learn.predict(img)
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  # Change each probability to a float, since Gradio doesn't support Tensors or NumPy
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  return dict(zip(categories, map(float, probs)))
21
 
 
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  # %% app.ipynb 10
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  image = gr.inputs.Image(shape=(192, 192))
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  label = gr.outputs.Label()
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  examples = ['images/ash.jpg', 'images/chestnut.jpg', 'images/ginkgo_biloba.jpg',
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  'images/silver_maple.jpg', 'images/willow_oak.jpg']
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+ # More useful args
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+ title = "Tree leaf classifier demo"
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+ description = "A tree leaf classifier demo, trained on images downloaded from DuckDuckGo. Created as a demo of HuggingFace Spaces and Gradio."
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+ article = "<p>From this blog post: <a href='https://briansigafoos.com/ml-quick-start' target='_blank'>Machine Learning quick start by Brian Sigafoos</a></p>"
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+ interpretation = 'default'
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+
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+ interface = gr.Interface(fn=classify_image, inputs=image, outputs=label,
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+ examples=examples, title=title, description=description,
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+ article=article, interpretation=interpretation)
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  interface.launch(inline=False)
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+