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Runtime error
Runtime error
yonatanbitton
commited on
Commit
β’
435f95e
1
Parent(s):
c4454c9
testing timeout
Browse files
app.py
CHANGED
@@ -7,6 +7,7 @@ wmtis = load_dataset("nlphuji/wmtis")['test']
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print(f"Loaded WMTIS, first example:")
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print(wmtis[0])
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dataset_size = len(wmtis) - 1
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IMAGE = 'image'
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IMAGE_DESIGNER = 'image_designer'
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@@ -20,8 +21,9 @@ IMAGE_ID = 'image_id'
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left_side_columns = [IMAGE]
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# left_side_columns = [IMAGE, DESIGNER_EXPLANATION, IMAGE_DESIGNER, IMAGE_ID]
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right_side_columns = [x for x in wmtis.features.keys() if x not in left_side_columns and x not in [QA]]
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enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
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emoji_to_label = {IMAGE: '
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QA: 'β, π€, π‘', IMAGE_ID: 'π, π, πΎ'}
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def func(index):
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example = wmtis[index]
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@@ -41,40 +43,90 @@ def get_instance_values(example):
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value = example[k]
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values.append(value)
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return values
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def list_to_string(lst):
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return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
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demo = gr.Blocks()
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-
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with gr.Column():
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slider = gr.Slider(minimum=0, maximum=dataset_size, step=1, label='index')
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with gr.Row():
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index = random.choice(range(0, dataset_size))
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example = wmtis[index]
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instance_values = get_instance_values(example)
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with gr.Column():
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# image_input = gr.Image(value=wmtis[index]["image"])
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inputs_left = []
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assert len(left_side_columns) == len(
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instance_values[:len(left_side_columns)]) # excluding the image & designer
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for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
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if key == IMAGE:
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input_k = gr.Image(value=wmtis[index]["image"], label=f"Image {emoji_to_label[key]}")
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else:
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label = key.capitalize().replace("_", " ")
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input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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inputs_left.append(input_k)
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with gr.Column():
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text_inputs_right = []
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assert len(right_side_columns) == len(instance_values[len(left_side_columns):]) # excluding the image & designer
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for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
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label = key.capitalize().replace("_", " ")
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text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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text_inputs_right.append(text_input_k)
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-
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demo.launch()
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print(f"Loaded WMTIS, first example:")
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print(wmtis[0])
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dataset_size = len(wmtis) - 1
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print(f"dataset_size: {dataset_size}")
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IMAGE = 'image'
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IMAGE_DESIGNER = 'image_designer'
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left_side_columns = [IMAGE]
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# left_side_columns = [IMAGE, DESIGNER_EXPLANATION, IMAGE_DESIGNER, IMAGE_ID]
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right_side_columns = [x for x in wmtis.features.keys() if x not in left_side_columns and x not in [QA]]
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# right_side_columns = ["designer_explanation", "image_designer"]
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enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
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emoji_to_label = {IMAGE: 'π', IMAGE_DESIGNER: 'π¨, π§βπ¨, π»', DESIGNER_EXPLANATION: 'π‘, π€, π§βπ¨', CROWD_CAPTIONS: 'π₯, π¬, π', CROWD_EXPLANATIONS: 'π₯, π‘, π€', CROWD_UNDERSPECIFIED_CAPTIONS: 'π₯, π¬, π',
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QA: 'β, π€, π‘', IMAGE_ID: 'π, π, πΎ'}
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def func(index):
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example = wmtis[index]
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value = example[k]
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values.append(value)
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return values
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def list_to_string(lst):
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return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
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# demo = gr.Blocks()
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#
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# with demo:
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# gr.Markdown("# Slide to iterate WMTIS")
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#
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# with gr.Column():
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# slider = gr.Slider(minimum=0, maximum=dataset_size, step=1, label='index')
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# with gr.Row():
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# # index = random.choice(range(0, dataset_size))
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# index = slider.value
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# example = wmtis[index]
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# instance_values = get_instance_values(example)
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# with gr.Column():
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# # image_input = gr.Image(value=wmtis[index]["image"])
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# inputs_left = []
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# assert len(left_side_columns) == len(
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# instance_values[:len(left_side_columns)]) # excluding the image & designer
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# for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
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# if key == IMAGE:
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# input_k = gr.Image(value=wmtis[index]["image"], label=f"Image {emoji_to_label[key]}")
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# else:
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# label = key.capitalize().replace("_", " ")
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# input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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# inputs_left.append(input_k)
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# with gr.Column():
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# text_inputs_right = []
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# assert len(right_side_columns) == len(instance_values[len(left_side_columns):]) # excluding the image & designer
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# for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
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# label = key.capitalize().replace("_", " ")
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# text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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# text_inputs_right.append(text_input_k)
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#
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# slider.change(func, inputs=[slider], outputs=inputs_left + text_inputs_right)
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#
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# demo.launch()
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from datasets import load_dataset
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import gradio as gr
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import os
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import random
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import time
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# auth_token = os.environ.get("token")
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# winoground = load_dataset("facebook/winoground", use_auth_token=auth_token)["test"]
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wmtis = load_dataset("nlphuji/wmtis")['test']
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target_size = (1024, 1024)
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def create_image_accordion_block(index):
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example = wmtis[index]
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instance_values = get_instance_values(example)
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assert len(left_side_columns) == len(
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instance_values[:len(left_side_columns)]) # excluding the image & designer
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for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
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if key == IMAGE:
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img = wmtis[index]["image"]
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img_resized = img.resize(target_size)
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gr.Image(value=img_resized, label=f"Image {emoji_to_label[key]}")
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else:
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label = key.capitalize().replace("_", " ")
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gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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with gr.Accordion("Open for More!", open=False):
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assert len(right_side_columns) == len(
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instance_values[len(left_side_columns):]) # excluding the image & designer
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for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
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label = key.capitalize().replace("_", " ")
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gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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columns_number = 3
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rows_number = 2
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tabs_number = 27
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with gr.Blocks() as demo:
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gr.Markdown(f"# Whoops! images by category")
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for tub_num in range(0, tabs_number):
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print(f"create tab:{tub_num}")
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with gr.Tab(f"Tab {tub_num}"):
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for row_num in range(0, rows_number):
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with gr.Row():
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for col_num in range(0, columns_number):
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with gr.Column():
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index = random.choice(range(0, dataset_size))
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create_image_accordion_block(index)
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demo.launch()
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app2.py
ADDED
@@ -0,0 +1,81 @@
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from datasets import load_dataset
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import gradio as gr
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import os
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import random
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wmtis = load_dataset("nlphuji/wmtis")['test']
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print(f"Loaded WMTIS, first example:")
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print(wmtis[0])
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dataset_size = len(wmtis) - 1
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IMAGE = 'image'
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IMAGE_DESIGNER = 'image_designer'
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DESIGNER_EXPLANATION = 'designer_explanation'
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CROWD_CAPTIONS = 'crowd_captions'
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CROWD_EXPLANATIONS = 'crowd_explanations'
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CROWD_UNDERSPECIFIED_CAPTIONS = 'crowd_underspecified_captions'
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# CROWD_NEGATIVE_EXPLANATIONS = 'crowd_negative_explanations'
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QA = 'question_answering_pairs'
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IMAGE_ID = 'image_id'
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left_side_columns = [IMAGE]
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# left_side_columns = [IMAGE, DESIGNER_EXPLANATION, IMAGE_DESIGNER, IMAGE_ID]
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right_side_columns = [x for x in wmtis.features.keys() if x not in left_side_columns and x not in [QA]]
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enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
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emoji_to_label = {IMAGE: 'πΌοΈ, π·, π', IMAGE_DESIGNER: 'π¨, π§βπ¨, π»', DESIGNER_EXPLANATION: 'π‘, π€, π§βπ¨', CROWD_CAPTIONS: 'π₯, π¬, π', CROWD_EXPLANATIONS: 'π₯, π‘, π€', CROWD_UNDERSPECIFIED_CAPTIONS: 'π₯, π¬, π',
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QA: 'β, π€, π‘', IMAGE_ID: 'π, π, πΎ'}
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def func(index):
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example = wmtis[index]
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values = get_instance_values(example)
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return values
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def get_instance_values(example):
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values = []
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for k in left_side_columns + right_side_columns:
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if k in enumerate_cols:
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value = list_to_string(example[k])
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elif k == QA:
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qa_list = [f"Q: {x[0]} A: {x[1]}" for x in example[k]]
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value = list_to_string(qa_list)
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else:
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value = example[k]
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values.append(value)
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return values
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def list_to_string(lst):
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return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
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demo = gr.Blocks()
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with demo:
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gr.Markdown("# Slide to iterate WMTIS")
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with gr.Column():
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slider = gr.Slider(minimum=0, maximum=dataset_size, step=1, label='index')
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with gr.Row():
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# index = random.choice(range(0, dataset_size))
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index = slider.label
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example = wmtis[index]
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instance_values = get_instance_values(example)
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with gr.Column():
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# image_input = gr.Image(value=wmtis[index]["image"])
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inputs_left = []
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assert len(left_side_columns) == len(
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instance_values[:len(left_side_columns)]) # excluding the image & designer
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for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
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if key == IMAGE:
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input_k = gr.Image(value=wmtis[index]["image"], label=f"Image {emoji_to_label[key]}")
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else:
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label = key.capitalize().replace("_", " ")
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input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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inputs_left.append(input_k)
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with gr.Column():
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text_inputs_right = []
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assert len(right_side_columns) == len(instance_values[len(left_side_columns):]) # excluding the image & designer
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for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
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label = key.capitalize().replace("_", " ")
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text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
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text_inputs_right.append(text_input_k)
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slider.change(func, inputs=[slider], outputs=inputs_left + text_inputs_right)
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demo.launch()
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