report top losses and confusion matrix

app.ipynb

@@ -44,7 +44,8 @@
     "}\n",
     "models = list(learners.keys())\n",
     "\n",
-    "active_model = learners[\"resnet-18\"]\n"
+    "active_name  = \"resnet-18\"\n",
+    "active_model = learners[active_name]\n"
    ]
   },
   {
@@ -64,8 +65,16 @@
     "def select_model(model_name):\n",
     "    if model_name not in models:\n",
     "        model_name = \"resnet-18\"\n",
-    "    active_model = learners[model_name]\n",
-    "    return model_name\n"
+    "    active_name = model_name\n",
+    "    active_model = learners[active_name]\n",
+    "    return model_name.upper()\n",
+    "\n",
+    "def update_matrix():\n",
+    "    return \"models/\" + active_name.replace('-','',1) + \"-confusion-matrix.png\"\n",
+    "    \n",
+    "def update_losses():\n",
+    "    return \"models/\" + active_name.replace('-','',1) + \"-top-losses.png\"\n",
+    "    "
    ]
   },
   {
@@ -493,6 +502,12 @@
     "#| export\n",
     "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",
     "\n",
+    "model_matrix = [ 'models/resnet101-confusion-matrix.png', 'models/resnet18-confusion-matrix.png',  'models/resnet50-confusion-matrix.png',\n",
+    "'models/resnet152-confusion-matrix.png', 'models/resnet34-confusion-matrix.png' ]\n",
+    "\n",
+    "model_losses = [ 'models/resnet101-top-losses.png', 'models/resnet18-top-losses.png',  'models/resnet50-top-losses.png',\n",
+    "'models/resnet152-top-losses.png', 'models/resnet34-top-losses.png' ]\n",
+    "\n",
     "demo = gr.Blocks()\n",
     "with demo:\n",
     "    with gr.Column(variant=\"panel\"):\n",
@@ -501,11 +516,18 @@
     "        btnClassify = gr.Button(\"Classify\")\n",
     "    with gr.Column(variant=\"panel\"):\n",
     "        selected = gr.outputs.Textbox(label=\"Active Model\")\n",
+    "        with gr.Row(equal_height=True):\n",
+    "            matrix=gr.outputs.Image(type='filepath', label=\"Confusion Matrix\")\n",
+    "            losses=gr.outputs.Image(type='filepath', label=\"Top Losses\")\n",
     "        result = gr.outputs.Label(label=\"Result\")\n",
     "        \n",
     "    model.change(fn=select_model, inputs=model, outputs=selected)\n",
     "    btnClassify.click(fn=classify_image, inputs=image, outputs=result)\n",
     "    img_gallery = gr.Examples(examples=example_images, inputs=image)\n",
+    "    matrix_gallery = gr.Examples(examples=model_matrix, label='Models Confusion Matrix', inputs=matrix)\n",
+    "    loss_gallery = gr.Examples(examples=model_losses, label='Models Top Losses', inputs=losses)\n",
+    "    result.change(fn=update_matrix, outputs=matrix)\n",
+    "    result.change(fn=update_losses, outputs=losses)\n",
     "\n",
     "demo.launch(debug=True, inline=False)\n",
     "    # intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )\n",
@@ -515,39 +537,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "id": "cab071f9-7c3b-4b35-a0d1-3687731ffce5",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Export successful\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import nbdev\n",
     "nbdev.export.nb_export('app.ipynb', './')\n",
     "print('Export successful')"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c7e6ddfb-9919-4a35-aac7-674d6fc5fd96",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e56bc359-81c7-4e70-a84a-5f81a0713cd3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

app.py

@@ -1,8 +1,8 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
 
 # %% auto 0
-__all__ = ['title', 'description', 'learners', 'models', 'active_model', 'example_images', 'demo', 'classify_image',
-           'select_model']
+__all__ = ['title', 'description', 'learners', 'models', 'active_name', 'active_model', 'example_images', 'model_matrix',
+           'model_losses', 'demo', 'classify_image', 'select_model', 'update_matrix', 'update_losses']
 
 # %% app.ipynb 1
 from fastai.vision.all import *
@@ -23,7 +23,8 @@ learners = {
 }
 models = list(learners.keys())
 
-active_model = learners["resnet-18"]
+active_name  = "resnet-18"
+active_model = learners[active_name]
 
 
 # %% app.ipynb 3
@@ -35,13 +36,26 @@ def classify_image(img):
 def select_model(model_name):
     if model_name not in models:
         model_name = "resnet-18"
-    active_model = learners[model_name]
-    return model_name
+    active_name = model_name
+    active_model = learners[active_name]
+    return model_name.upper()
 
+def update_matrix():
+    return "models/" + active_name.replace('-','',1) + "-confusion-matrix.png"
+    
+def update_losses():
+    return "models/" + active_name.replace('-','',1) + "-top-losses.png"
+    
 
 # %% app.ipynb 5
 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' ]
 
+model_matrix = [ 'models/resnet101-confusion-matrix.png', 'models/resnet18-confusion-matrix.png',  'models/resnet50-confusion-matrix.png',
+'models/resnet152-confusion-matrix.png', 'models/resnet34-confusion-matrix.png' ]
+
+model_losses = [ 'models/resnet101-top-losses.png', 'models/resnet18-top-losses.png',  'models/resnet50-top-losses.png',
+'models/resnet152-top-losses.png', 'models/resnet34-top-losses.png' ]
+
 demo = gr.Blocks()
 with demo:
     with gr.Column(variant="panel"):
@@ -50,11 +64,18 @@ with demo:
         btnClassify = gr.Button("Classify")
     with gr.Column(variant="panel"):
         selected = gr.outputs.Textbox(label="Active Model")
+        with gr.Row(equal_height=True):
+            matrix=gr.outputs.Image(type='filepath', label="Confusion Matrix")
+            losses=gr.outputs.Image(type='filepath', label="Top Losses")
         result = gr.outputs.Label(label="Result")
         
     model.change(fn=select_model, inputs=model, outputs=selected)
     btnClassify.click(fn=classify_image, inputs=image, outputs=result)
     img_gallery = gr.Examples(examples=example_images, inputs=image)
+    matrix_gallery = gr.Examples(examples=model_matrix, label='Models Confusion Matrix', inputs=matrix)
+    loss_gallery = gr.Examples(examples=model_losses, label='Models Top Losses', inputs=losses)
+    result.change(fn=update_matrix, outputs=matrix)
+    result.change(fn=update_losses, outputs=losses)
 
 demo.launch(debug=True, inline=False)
     # intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=example_images, title=title, description=description )