Add more elements to space's interface.

README.md

@@ -4,10 +4,12 @@ emoji: 🌊
 colorFrom: blue
 colorTo: gray
 sdk: gradio
+python_version: 3.10.7
 sdk_version: 3.3.1
 app_file: app.py
 pinned: false
 license: apache-2.0
+tags: [disaster relief, image classification]
 ---
 
 The workflow works!!!

app.ipynb

@@ -112,6 +112,15 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Create classification function."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -119,7 +128,7 @@
    "source": [
     "#|export\n",
     "\n",
-    "categories = ('Not Flooded', 'Flooded')\n",
+    "categories = 'Not Flooded', 'Flooded',\n",
     "\n",
     "def classify_image(image):\n",
     "    prediction, index, probabilities = learner.predict(image)\n",
@@ -165,9 +174,18 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Intialize attributes for the interface."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 29,
    "outputs": [],
    "source": [
     "#|export\n",
@@ -175,7 +193,19 @@
     "image = gr.Image()\n",
     "label = gr.Label()\n",
     "examples = [str(image_path) for image_path in Path('images/example_images')\n",
-    ".rglob('*.jpeg')]"
+    ".rglob('*.jpeg')]\n",
+    "\n",
+    "title = 'Flood Classifier'\n",
+    "description = \"An image classifier that can tell whether an image is flooded \" \\\n",
+    "              \"or not. Works well with images that have a top-down/aeiral \" \\\n",
+    "              \"view of the land below.\" \\\n",
+    "              \"This model was trained on the ResNet18 architecture and the \" \\\n",
+    "              \"fastai library.\" \\\n",
+    "              \"Check out the associated blog post with the link below!\"\n",
+    "article = \"<p style='text-align: center; font-size: 36px'><a \" \\\n",
+    "          \"href='https://forbo7.github\" \\\n",
+    "          \".io/ForBlog/fastai/image%20classification/2022/09/12/Detecting\" \\\n",
+    "          \"-Floods-for-Disaster-Relief.html' targets='_blank'>Blog Post</a></p>'\""
    ],
    "metadata": {
     "collapsed": false
@@ -201,24 +231,33 @@
     "collapsed": false
    }
   },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "## Create the interface."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 28,
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7860\n",
+      "Running on local URL:  http://127.0.0.1:7869\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
     },
     {
      "data": {
-      "text/plain": "(<gradio.routes.App at 0x16e4f7e20>, 'http://127.0.0.1:7860/', None)"
+      "text/plain": "(<gradio.routes.App at 0x29d4a8040>, 'http://127.0.0.1:7869/', None)"
      },
-     "execution_count": 10,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -226,8 +265,11 @@
    "source": [
     "#|export\n",
     "\n",
-    "interface = gr.Interface(fn=classify_image, inputs='image', outputs='label', examples=examples)\n",
-    "interface.launch(inline=False)"
+    "# Perhaps I can make the interface below with **kwargs?\n",
+    "interface = gr.Interface(fn=classify_image, inputs='image', outputs='label',\n",
+    "                         examples=examples, title=title,\n",
+    "                         description=description, article=article)\n",
+    "interface.launch(inline=False, enable_queue=True)"
    ],
    "metadata": {
     "collapsed": false
@@ -244,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 30,
    "outputs": [],
    "source": [
     "from nbdev.export import nb_export"
@@ -255,7 +297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 31,
    "outputs": [],
    "source": [
     "nb_export('app.ipynb', '.')"

app.py

@@ -1,7 +1,8 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = ['learner', 'categories', 'image', 'label', 'examples', 'interface', 'classify_image']
+__all__ = ['learner', 'categories', 'image', 'label', 'examples', 'title', 'description', 'article', 'interface',
+           'classify_image']
 
 # %% app.ipynb 2
 import gradio as gr
@@ -10,19 +11,34 @@ from fastai.vision.all import *
 # %% app.ipynb 5
 learner = load_learner('model/flood_classifier.pkl')
 
-# %% app.ipynb 7
-categories = ('Not Flooded', 'Flooded')
+# %% app.ipynb 8
+categories = 'Not Flooded', 'Flooded',
 
 def classify_image(image):
     prediction, index, probabilities = learner.predict(image)
     return dict(zip(categories, map(float, probabilities)))
 
-# %% app.ipynb 9
+# %% app.ipynb 11
 image = gr.Image()
 label = gr.Label()
 examples = [str(image_path) for image_path in Path('images/example_images')
 .rglob('*.jpeg')]
 
-# %% app.ipynb 11
-interface = gr.Interface(fn=classify_image, inputs='image', outputs='label', examples=examples)
-interface.launch(inline=False)
+title = 'Flood Classifier'
+description = "An image classifier that can tell whether an image is flooded " \
+              "or not. Works well with images that have a top-down/aeiral " \
+              "view of the land below." \
+              "This model was trained on the ResNet18 architecture and the " \
+              "fastai library." \
+              "Check out the associated blog post with the link below!"
+article = "<p style='text-align: center; font-size: 36px'><a " \
+          "href='https://forbo7.github" \
+          ".io/ForBlog/fastai/image%20classification/2022/09/12/Detecting" \
+          "-Floods-for-Disaster-Relief.html' targets='_blank'>Blog Post</a></p>'"
+
+# %% app.ipynb 14
+# Perhaps I can make the interface below with **kwargs?
+interface = gr.Interface(fn=classify_image, inputs='image', outputs='label',
+                         examples=examples, title=title,
+                         description=description, article=article)
+interface.launch(inline=False, enable_queue=True)

flagged/log.csv

@@ -0,0 +1,4 @@
+image,output,flag,username,timestamp
+/Users/salmannaqvi/DataspellProjects/FloodDetector/flagged/image/tmpvd6_25r3.jpg,/Users/salmannaqvi/DataspellProjects/FloodDetector/flagged/output/tmp12mf7l3w.json,,,2022-09-17 19:10:43.606594
+,,,,2022-09-17 19:19:07.108909
+/Users/salmannaqvi/DataspellProjects/FloodDetector/flagged/image/tmp6dcva8py.jpg,,,,2022-09-17 19:19:09.166293

flagged/output/tmp12mf7l3w.json

@@ -0,0 +1 @@
+{"label": "Flooded", "confidences": [{"label": "Flooded", "confidence": 0.531377911567688}, {"label": "Not Flooded", "confidence": 0.4686220586299896}]}

runtime.txt

@@ -0,0 +1 @@
+python-3.10.7