cutomize gardio app

app.ipynb

@@ -191,9 +191,32 @@
     "classify_image(im)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "491f209b",
+   "metadata": {},
+   "source": [
+    "# Customizing Gradio app"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 8,
+   "id": "03269867",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "title = \"Cat or Dog Classifier\"\n",
+    "description = \"A Cat or Dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces.\"\n",
+    "article=\"<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>\"\n",
+    "interpretation='default'\n",
+    "enable_queue=True"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
    "id": "6ed6b1ad",
    "metadata": {},
    "outputs": [
@@ -208,6 +231,8 @@
       "/home/yehao_ubuntu/mambaforge/lib/python3.10/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
       "  warnings.warn(\n",
       "/home/yehao_ubuntu/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
+      "  warnings.warn(value)\n",
+      "/home/yehao_ubuntu/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `enable_queue` is deprecated in `Interface()`, please use it within `launch()` instead.\n",
       "  warnings.warn(value)\n"
      ]
     },
@@ -215,7 +240,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7861\n",
+      "Running on local URL:  http://127.0.0.1:7860\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -224,7 +249,7 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 8,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -235,7 +260,7 @@
     "label = gr.outputs.Label()\n",
     "examples = [\"dog1.jpg\", \"dog2.jpg\", \"dog3.jpg\", \"cat1.jpg\", \"cat2.jpg\"]\n",
     "\n",
-    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
+    "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title=title, description=description, article=article, interpretation=interpretation, enable_queue=enable_queue)\n",
     "intf.launch(inline=False)"
    ]
   },
@@ -249,7 +274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "83142b64",
    "metadata": {},
    "outputs": [

app.py

@@ -1,7 +1,8 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'is_cat', 'classify_image']
+__all__ = ['learn', 'categories', 'title', 'description', 'article', 'interpretation', 'enable_queue', 'image', 'label',
+           'examples', 'intf', 'is_cat', 'classify_image']
 
 # %% app.ipynb 1
 from fastai.vision.all import *
@@ -20,10 +21,17 @@ def classify_image(img):
     pred, idx, probs = learn.predict(img)
     return dict(zip(categories, map(float, probs)))
 
-# %% app.ipynb 7
+# %% app.ipynb 8
+title = "Cat or Dog Classifier"
+description = "A Cat or Dog classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
+interpretation='default'
+enable_queue=True
+
+# %% app.ipynb 9
 image = gr.inputs.Image(shape=(192, 192))
 label = gr.outputs.Label()
 examples = ["dog1.jpg", "dog2.jpg", "dog3.jpg", "cat1.jpg", "cat2.jpg"]
 
-intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples, title=title, description=description, article=article, interpretation=interpretation, enable_queue=enable_queue)
 intf.launch(inline=False)

flagged/log.csv

@@ -0,0 +1,2 @@
+img,output,flag,username,timestamp
+/home/yehao_ubuntu/testing2/flagged/img/tmpj8t3miuy.jpg,/home/yehao_ubuntu/testing2/flagged/output/tmpvesdv1ch.json,,,2023-04-22 22:44:25.804158

flagged/output/tmpvesdv1ch.json

@@ -0,0 +1 @@
+{"label": "Cat", "confidences": [{"label": "Cat", "confidence": 1}, {"label": "Dog", "confidence": 2.119180919635255e-08}]}

requirements.txt

@@ -2,4 +2,5 @@ fastai
 torch
 gradio
 numpy
-pandas
+pandas
+scikit-image