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| import math | |
| from datasets import load_dataset | |
| import gradio as gr | |
| import os | |
| auth_token = os.environ.get("auth_token") | |
| whoops = load_dataset("nlphuji/whoops", use_auth_token=auth_token)['test'] | |
| # print(f"Loaded WHOOPS!, first example:") | |
| # print(whoops[0]) | |
| dataset_size = len(whoops) | |
| IMAGE = 'image' | |
| IMAGE_DESIGNER = 'image_designer' | |
| DESIGNER_EXPLANATION = 'designer_explanation' | |
| CROWD_CAPTIONS = 'crowd_captions' | |
| CROWD_EXPLANATIONS = 'crowd_explanations' | |
| CROWD_UNDERSPECIFIED_CAPTIONS = 'crowd_underspecified_captions' | |
| QA = 'question_answering_pairs' | |
| IMAGE_ID = 'image_id' | |
| SELECTED_CAPTION = 'selected_caption' | |
| COMMONSENSE_CATEGORY = 'commonsense_category' | |
| left_side_columns = [IMAGE] | |
| right_side_columns = [x for x in whoops.features.keys() if x not in left_side_columns] | |
| 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: '📝, 👌, 💬'} | |
| # batch_size = 16 | |
| batch_size = 8 | |
| target_size = (1024, 1024) | |
| def func(index): | |
| start_index = index * batch_size | |
| end_index = start_index + batch_size | |
| all_examples = [whoops[index] for index in list(range(start_index, end_index))] | |
| values_lst = [] | |
| for example_idx, example in enumerate(all_examples): | |
| values = get_instance_values(example) | |
| values_lst += values | |
| return values_lst | |
| def get_instance_values(example): | |
| values = [] | |
| for k in left_side_columns + right_side_columns: | |
| if k == IMAGE: | |
| value = example["image"].resize(target_size) | |
| elif 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)]) | |
| demo = gr.Blocks() | |
| def get_col(): | |
| instance_values = get_instance_values(example) | |
| with gr.Column(): | |
| 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: | |
| img_resized = example["image"].resize(target_size) | |
| input_k = gr.Image(value=img_resized, label=example['commonsense_category']) | |
| 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.Accordion("Click for details", open=False): | |
| 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) | |
| return inputs_left, text_inputs_right | |
| with demo: | |
| gr.Markdown("# Slide to iterate WHOOPS!") | |
| with gr.Column(): | |
| num_batches = math.ceil(dataset_size / batch_size) | |
| slider = gr.Slider(minimum=0, maximum=num_batches, step=1, label=f'Page (out of {num_batches})') | |
| with gr.Row(): | |
| index = slider.value | |
| start_index = 0 * batch_size | |
| end_index = start_index + batch_size | |
| all_examples = [whoops[index] for index in list(range(start_index, end_index))] | |
| all_inputs_left_right = [] | |
| for example_idx, example in enumerate(all_examples): | |
| inputs_left, text_inputs_right = get_col() | |
| inputs_left_right = inputs_left + text_inputs_right | |
| all_inputs_left_right += inputs_left_right | |
| slider.change(func, inputs=[slider], outputs=all_inputs_left_right) | |
| demo.launch() | |