update

app.py

@@ -16,6 +16,15 @@ all_origins = set()
 all_labels = set()
 dataset_df = None
 
+beautiful_dataset_names = {
+    "imagenet": "ImageNet",
+    "imagenet_a": "ImageNet-A",
+    "imagenet_r": "ImageNet-R",
+    "imagenet_sketch": "ImageNet-Sketch",
+    "objectnet": "ObjectNet",
+    "imagenet_v2": "ImageNet-V2",
+}
+
 
 def process_image(i):
     global all_origins
@@ -61,6 +70,26 @@ else:
         dataset_df.to_pickle("dataset.pkl")
 
 
+def get_values_for_the_slice(slice_df):
+    returned_values = []
+    for row in slice_df.itertuples():
+        # returned_values.append(gr.update(value=row.preview))
+        labels = ", ".join(row.labels)
+        # replace _ with space
+        labels = labels.replace("_", " ")
+
+        dataset_name = beautiful_dataset_names[row.origin]
+
+        label_string = f"{labels} -  ({dataset_name})"
+        returned_values.append(gr.update(label=label_string, value=row.preview))
+        # returned_values.append(gr.update(value=beautiful_dataset_names[row.origin]))
+
+    if len(returned_values) < 16:
+        returned_values.extend([None] * (16 - len(returned_values)))
+
+    return returned_values
+
+
 def get_slice(origin, label):
     global dataset_df
 
@@ -74,20 +103,11 @@ def get_slice(origin, label):
 
     max_value = len(filtered_df) // 16
 
-    returned_values = []
-
     start_index = 0
     end_index = start_index + 16
 
     slice_df = filtered_df.iloc[start_index:end_index]
-
-    for row in slice_df.itertuples():
-        returned_values.append(gr.update(value=row.preview))
-        returned_values.append(gr.update(value=row.origin))
-        returned_values.append(gr.update(value=row.labels))
-
-    if len(returned_values) < 48:
-        returned_values.extend([None] * (48 - len(returned_values)))
+    returned_values = get_values_for_the_slice(slice_df)
 
     filtered_df = gr.Dataframe(filtered_df, datatype="markdown")
     return filtered_df, gr.update(maximum=max_value, value=0), *returned_values
@@ -105,32 +125,22 @@ def make_grid(grid_size):
             with gr.Column():
                 for col_counter in range(grid_size[1]):
                     item_image = gr.Image()
-                    with gr.Accordion("Click for details", open=False):
-                        item_source = gr.Textbox(label="Source Dataset")
-                        item_labels = gr.Textbox(label="Labels")
+                    # with gr.Accordion("Click for details", open=False):
+                    # item_source = gr.Textbox(label="Source Dataset")
 
                     list_of_components.append(item_image)
-                    list_of_components.append(item_source)
-                    list_of_components.append(item_labels)
+                    # list_of_components.append(item_source)
+                    # list_of_components.append(item_labels)
 
     return list_of_components
 
 
 def slider_upadte(slider, df):
-    returned_values = []
-
     start_index = (slider) * 16
     end_index = start_index + 16
 
     slice_df = df.iloc[start_index:end_index]
-
-    for row in slice_df.itertuples():
-        returned_values.append(gr.update(value=row.preview))
-        returned_values.append(gr.update(value=row.origin))
-        returned_values.append(gr.update(value=row.labels))
-
-    if len(returned_values) < 48:
-        returned_values.extend([None] * (48 - len(returned_values)))
+    returned_values = get_values_for_the_slice(slice_df)
 
     return returned_values
 
@@ -153,12 +163,12 @@ with gr.Blocks() as demo:
 
     with gr.Row():
         origin_dropdown = gr.Dropdown(all_origins, label="Origin")
-        label_dropdown = gr.Dropdown(all_labels, label="Label")
+        label_dropdown = gr.Dropdown(all_labels, label="Category")
     with gr.Row():
         show_btn = gr.Button("Show")
         reset_filters = gr.Button("Reset Filters")
 
-    preview_dataframe = gr.Dataframe(height=500, visible=False)
+    preview_dataframe = gr.Dataframe(visible=False)
 
     gr.Markdown("## Preview")
 

requirements.txt

@@ -2,4 +2,5 @@ transformers
 datasets
 tqdm
 numpy
-pandas
+pandas
+tqdm