Added default images and descriptions

Signed-off-by: Kieran Fraser <[email protected]>

app.py

@@ -59,6 +59,26 @@ model = transformers.AutoModelForImageClassification.from_pretrained(
         num_labels=10
     )
 
+def default_clean():
+    return [('./data/default/clean/0_fish.png', 'fish'),
+            ('./data/default/clean/1_fish.png', 'fish'),
+            ('./data/default/clean/2_fish.png', 'church'),
+            ('./data/default/clean/3_fish.png', 'fish'),
+            ('./data/default/clean/4_fish.png', 'church'),
+            ('./data/default/clean/5_fish.png', 'fish'),
+            ('./data/default/clean/6_fish.png', 'fish'),
+            ('./data/default/clean/7_fish.png', 'fish')]
+    
+def default_poisoned():
+    return [('./data/default/poisoned/0_fish.png', 'church'),
+            ('./data/default/poisoned/1_fish.png', 'church'),
+            ('./data/default/poisoned/2_fish.png', 'church'),
+            ('./data/default/poisoned/3_fish.png', 'church'),
+            ('./data/default/poisoned/4_fish.png', 'church'),
+            ('./data/default/poisoned/5_fish.png', 'church'),
+            ('./data/default/poisoned/6_fish.png', 'church'),
+            ('./data/default/poisoned/7_fish.png', 'church')]
+
 def sample_imagenette():
     import torchvision
     label_names = [
@@ -311,8 +331,8 @@ with gr.Blocks(css=css, theme='Tshackelton/IBMPlex-DenseReadable') as demo:
                                         'parachutte',], value='church')
             eval_btn_patch = gr.Button("Evaluate ✨", elem_classes="eval-bt")
         with gr.Column(scale=10):
-            clean_gallery = gr.Gallery(label="Clean", preview=False, show_download_button=True, height=600)
-            clean_accuracy = gr.Number(label="Clean Accuracy", precision=2)
+            clean_gallery = gr.Gallery(default_clean(), label="Clean", preview=False, show_download_button=True, height=600)
+            clean_accuracy = gr.Number(0.97, label="Clean Accuracy", precision=2, info="The percent of correctly classified images without trigger.")
         with gr.Column(scale=1, min_width=0, elem_classes='symbols'):
             gr.Markdown('''➕''')
         with gr.Column(scale=3, elem_classes='symbols'):
@@ -320,8 +340,8 @@ with gr.Blocks(css=css, theme='Tshackelton/IBMPlex-DenseReadable') as demo:
         with gr.Column(scale=1, min_width=0):
             gr.Markdown('''🟰''', elem_classes='symbols')
         with gr.Column(scale=10):
-            poison_gallery = gr.Gallery(label="Poisoned", preview=False, show_download_button=True, height=600)
-            poison_success = gr.Number(label="Poison Success", precision=2)
+            poison_gallery = gr.Gallery(default_poisoned(), label="Poisoned", preview=False, show_download_button=True, height=600)
+            poison_success = gr.Number(1.0, label="Poison Success", precision=2, info="The percent of images with trigger classified as the target.")
         
     eval_btn_patch.click(clf_poison_evaluate, inputs=[attack, trigger_image, target_class],
                 outputs=[clean_gallery, poison_gallery, clean_accuracy, poison_success])