testing timeout

.gitignore

@@ -11,6 +11,8 @@ inspectionProfiles
 inspectionProfiles/
 
 debug_dataset.py
+app2.py
+app_tabs.py
 
 # C extensions
 *.so

app.py

@@ -1,13 +1,13 @@
-from datasets import load_dataset
-import gradio as gr
-import os
 import random
 
-wmtis = load_dataset("nlphuji/wmtis")['test']
+import gradio as gr
+from datasets import load_dataset
+
+whoops = load_dataset("nlphuji/whoops")['test']
 print(f"Loaded WMTIS, first example:")
-print(wmtis[0])
-dataset_size = len(wmtis) - 1
-print(f"dataset_size: {dataset_size}")
+print(whoops[0])
+dataset_size = len(whoops)
+print(f"all dataset size: {dataset_size}")
 
 IMAGE = 'image'
 IMAGE_DESIGNER = 'image_designer'
@@ -15,18 +15,21 @@ DESIGNER_EXPLANATION = 'designer_explanation'
 CROWD_CAPTIONS = 'crowd_captions'
 CROWD_EXPLANATIONS = 'crowd_explanations'
 CROWD_UNDERSPECIFIED_CAPTIONS = 'crowd_underspecified_captions'
-# CROWD_NEGATIVE_EXPLANATIONS = 'crowd_negative_explanations'
+SELECTED_CAPTION = 'selected_caption'
+COMMONSENSE_CATEGORY = 'commonsense_category'
 QA = 'question_answering_pairs'
 IMAGE_ID = 'image_id'
 left_side_columns = [IMAGE]
-# left_side_columns = [IMAGE, DESIGNER_EXPLANATION, IMAGE_DESIGNER, IMAGE_ID]
-right_side_columns = [x for x in wmtis.features.keys() if x not in left_side_columns and x not in [QA]]
-# right_side_columns = ["designer_explanation", "image_designer"]
+right_side_columns = [x for x in whoops.features.keys() if x not in left_side_columns and x not in [QA]]
 enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
-emoji_to_label = {IMAGE: '🌄', IMAGE_DESIGNER: '🎨, 🧑‍🎨, 💻', DESIGNER_EXPLANATION: '💡, 🤔, 🧑‍🎨', CROWD_CAPTIONS: '👥, 💬, 📝', CROWD_EXPLANATIONS: '👥, 💡, 🤔', CROWD_UNDERSPECIFIED_CAPTIONS: '👥, 💬, 👎',
-                  QA: '❓, 🤔, 💡', IMAGE_ID: '🔍, 📄, 💾'}
+emoji_to_label = {IMAGE_DESIGNER: '🎨, 🧑‍🎨, 💻', DESIGNER_EXPLANATION: '💡, 🤔, 🧑‍🎨',
+                  CROWD_CAPTIONS: '👥, 💬, 📝', CROWD_EXPLANATIONS: '👥, 💡, 🤔', CROWD_UNDERSPECIFIED_CAPTIONS: '👥, 💬, 👎',
+                  QA: '❓, 🤔, 💡', IMAGE_ID: '🔍, 📄, 💾', COMMONSENSE_CATEGORY: '🤔, 📚, 💡', SELECTED_CAPTION: '📝, 👌, 💬'}
+target_size = (1024, 1024)
+
+
 def func(index):
-    example = wmtis[index]
+    example = whoops[index]
     values = get_instance_values(example)
     return values
 
@@ -44,69 +47,24 @@ def get_instance_values(example):
         values.append(value)
     return values
 
-def list_to_string(lst):
-    return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
-
-# demo = gr.Blocks()
-#
-# with demo:
-#     gr.Markdown("# Slide to iterate WMTIS")
-#
-#     with gr.Column():
-#         slider = gr.Slider(minimum=0, maximum=dataset_size, step=1, label='index')
-#         with gr.Row():
-#             # index = random.choice(range(0, dataset_size))
-#             index = slider.value
-#             example = wmtis[index]
-#             instance_values = get_instance_values(example)
-#             with gr.Column():
-#                 # image_input = gr.Image(value=wmtis[index]["image"])
-#                 inputs_left = []
-#                 assert len(left_side_columns) == len(
-#                     instance_values[:len(left_side_columns)])  # excluding the image & designer
-#                 for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
-#                     if key == IMAGE:
-#                         input_k = gr.Image(value=wmtis[index]["image"], label=f"Image {emoji_to_label[key]}")
-#                     else:
-#                         label = key.capitalize().replace("_", " ")
-#                         input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
-#                     inputs_left.append(input_k)
-#             with gr.Column():
-#                 text_inputs_right = []
-#                 assert len(right_side_columns) == len(instance_values[len(left_side_columns):]) # excluding the image & designer
-#                 for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
-#                     label = key.capitalize().replace("_", " ")
-#                     text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
-#                     text_inputs_right.append(text_input_k)
-#
-#     slider.change(func, inputs=[slider], outputs=inputs_left + text_inputs_right)
-#
-# demo.launch()
 
-from datasets import load_dataset
-import gradio as gr
-import os
-import random
-import time
-# auth_token = os.environ.get("token")
-# winoground = load_dataset("facebook/winoground", use_auth_token=auth_token)["test"]
-wmtis = load_dataset("nlphuji/wmtis")['test']
-target_size = (1024, 1024)
+def list_to_string(lst):
+    return '\n'.join(['{}. {}'.format(i + 1, item) for i, item in enumerate(lst)])
 
-def create_image_accordion_block(index):
-    example = wmtis[index]
+def plot_image(index):
+    example = whoops[index]
     instance_values = get_instance_values(example)
     assert len(left_side_columns) == len(
         instance_values[:len(left_side_columns)])  # excluding the image & designer
     for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
         if key == IMAGE:
-            img = wmtis[index]["image"]
+            img = whoops[index]["image"]
             img_resized = img.resize(target_size)
-            gr.Image(value=img_resized, label=f"Image {emoji_to_label[key]}")
+            gr.Image(value=img_resized, label=whoops[index]['commonsense_category'])
         else:
             label = key.capitalize().replace("_", " ")
             gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
-    with gr.Accordion("Open for More!", open=False):
+    with gr.Accordion("Click for details", open=False):
         assert len(right_side_columns) == len(
             instance_values[len(left_side_columns):])  # excluding the image & designer
         for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
@@ -114,19 +72,18 @@ def create_image_accordion_block(index):
             gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
 
 
-columns_number = 3
-rows_number = 2
-tabs_number = 27
+columns_number = 4
+# rows_number = int(dataset_size / columns_number)
+rows_number = 30
+whoops_sample = whoops.shuffle().select(range(0, columns_number * rows_number))
+index = 0
 
 with gr.Blocks() as demo:
-    gr.Markdown(f"# Whoops! images by category")
-    for tub_num in range(0, tabs_number):
-        print(f"create tab:{tub_num}")
-        with gr.Tab(f"Tab {tub_num}"):
-            for row_num in range(0, rows_number):
-                with gr.Row():
-                    for col_num in range(0, columns_number):
-                        with gr.Column():
-                            index = random.choice(range(0, dataset_size))
-                            create_image_accordion_block(index)
+    gr.Markdown(f"# WHOOPS! Dataset Explorer")
+    for row_num in range(0, rows_number):
+        with gr.Row():
+            for col_num in range(0, columns_number):
+                with gr.Column():
+                    plot_image(index)
+                    index += 1
 demo.launch()

app_tabs.py

@@ -0,0 +1,90 @@
+import random
+
+import gradio as gr
+from datasets import load_dataset
+
+wmtis = load_dataset("nlphuji/whoops")['test']
+print(f"Loaded WMTIS, first example:")
+print(wmtis[0])
+dataset_size = len(wmtis)
+print(f"dataset_size: {dataset_size}")
+
+IMAGE = 'image'
+IMAGE_DESIGNER = 'image_designer'
+DESIGNER_EXPLANATION = 'designer_explanation'
+CROWD_CAPTIONS = 'crowd_captions'
+CROWD_EXPLANATIONS = 'crowd_explanations'
+CROWD_UNDERSPECIFIED_CAPTIONS = 'crowd_underspecified_captions'
+SELECTED_CAPTION = 'selected_caption'
+COMMONSENSE_CATEGORY = 'commonsense_category'
+QA = 'question_answering_pairs'
+IMAGE_ID = 'image_id'
+left_side_columns = [IMAGE]
+right_side_columns = [x for x in wmtis.features.keys() if x not in left_side_columns and x not in [QA]]
+enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
+emoji_to_label = {IMAGE_DESIGNER: '🎨, 🧑‍🎨, 💻', DESIGNER_EXPLANATION: '💡, 🤔, 🧑‍🎨',
+                  CROWD_CAPTIONS: '👥, 💬, 📝', CROWD_EXPLANATIONS: '👥, 💡, 🤔', CROWD_UNDERSPECIFIED_CAPTIONS: '👥, 💬, 👎',
+                  QA: '❓, 🤔, 💡', IMAGE_ID: '🔍, 📄, 💾', COMMONSENSE_CATEGORY: '🤔, 📚, 💡', SELECTED_CAPTION: '📝, 👌, 💬'}
+target_size = (1024, 1024)
+
+
+def func(index):
+    example = wmtis[index]
+    values = get_instance_values(example)
+    return values
+
+
+def get_instance_values(example):
+    values = []
+    for k in left_side_columns + right_side_columns:
+        if k in enumerate_cols:
+            value = list_to_string(example[k])
+        elif k == QA:
+            qa_list = [f"Q: {x[0]} A: {x[1]}" for x in example[k]]
+            value = list_to_string(qa_list)
+        else:
+            value = example[k]
+        values.append(value)
+    return values
+
+
+def list_to_string(lst):
+    return '\n'.join(['{}. {}'.format(i + 1, item) for i, item in enumerate(lst)])
+
+def create_image_accordion_block(index):
+    example = wmtis[index]
+    instance_values = get_instance_values(example)
+    assert len(left_side_columns) == len(
+        instance_values[:len(left_side_columns)])  # excluding the image & designer
+    for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
+        if key == IMAGE:
+            img = wmtis[index]["image"]
+            img_resized = img.resize(target_size)
+            gr.Image(value=img_resized, label=f"Image {emoji_to_label[key]}")
+        else:
+            label = key.capitalize().replace("_", " ")
+            gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
+    with gr.Accordion("Open for More!", open=False):
+        assert len(right_side_columns) == len(
+            instance_values[len(left_side_columns):])  # excluding the image & designer
+        for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
+            label = key.capitalize().replace("_", " ")
+            gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
+
+
+columns_number = 2
+rows_number = 2
+tabs_number = 27
+
+with gr.Blocks() as demo:
+    gr.Markdown(f"# Whoops! images by category")
+    for tub_num in range(0, tabs_number):
+        print(f"create tab:{tub_num}")
+        with gr.Tab(f"Tab {tub_num}"):
+            for row_num in range(0, rows_number):
+                with gr.Row():
+                    for col_num in range(0, columns_number):
+                        with gr.Column():
+                            index = random.choice(range(0, dataset_size))
+                            create_image_accordion_block(index)
+demo.launch()