Spaces:
Runtime error
Runtime error
| import os | |
| from pathlib import Path | |
| import sqlite3 | |
| import gradio as gr | |
| from datasets import Dataset, DatasetDict | |
| # Connect to SQLite database | |
| conn = sqlite3.connect('votes.db') | |
| c = conn.cursor() | |
| # Create table if it doesn't exist | |
| c.execute('''CREATE TABLE IF NOT EXISTS votes | |
| (filename TEXT, uap_votes INTEGER, not_uap_votes INTEGER)''') | |
| # Load image data from the folder | |
| dataset_path = os.path.join(os.getcwd(), 'content/nuforc_reports') | |
| dataset = DatasetDict.from_disk(dataset_path) | |
| image_files = [example['file'] for example in dataset['train']] | |
| # Function to vote for an image | |
| def vote_for_image(filename, vote): | |
| if vote == 'UAP': | |
| c.execute("UPDATE votes SET uap_votes = uap_votes + 1 WHERE filename = ?", (filename,)) | |
| elif vote == 'Not UAP': | |
| c.execute("UPDATE votes SET not_uap_votes = not_uap_votes + 1 WHERE filename = ?", (filename,)) | |
| conn.commit() | |
| # Get vote counts for an image | |
| def get_vote_counts(filename): | |
| c.execute("SELECT uap_votes, not_uap_votes FROM votes WHERE filename = ?", (filename,)) | |
| row = c.fetchone() | |
| if row: | |
| return row | |
| else: | |
| c.execute("INSERT INTO votes (filename, uap_votes, not_uap_votes) VALUES (?, 0, 0)", (filename,)) | |
| conn.commit() | |
| return (0, 0) | |
| # Gradio interface | |
| image_select = gr.Dropdown(image_files, label="Select an image") | |
| votes = gr.RenderedHTML() | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| image = gr.Image(value=f"{dataset_path}/{image_files[0]}", shape=(400, 400)) | |
| with gr.Column(): | |
| uap_vote = gr.Button("UAP") | |
| not_uap_vote = gr.Button("Not UAP") | |
| image_select.change(lambda x: f"{dataset_path}/{x}", inputs=image_select, outputs=image) | |
| uap_vote.click(vote_for_image, inputs=[image_select, gr.Const("UAP")], outputs=None) | |
| not_uap_vote.click(vote_for_image, inputs=[image_select, gr.Const("Not UAP")], outputs=None) | |
| vote_counts = gr.Column() | |
| image_select.change(lambda x: gr.Markdown(f"**UAP votes**: {get_vote_counts(x)[0]}\n**Not UAP votes**: {get_vote_counts(x)[1]}"), inputs=image_select, outputs=vote_counts) | |
| demo.launch()import os | |
| from pathlib import Path | |
| import sqlite3 | |
| import gradio as gr | |
| from datasets import Dataset, DatasetDict | |
| # Connect to SQLite database | |
| conn = sqlite3.connect('votes.db') | |
| c = conn.cursor() | |
| # Create table if it doesn't exist | |
| c.execute('''CREATE TABLE IF NOT EXISTS votes | |
| (filename TEXT, uap_votes INTEGER, not_uap_votes INTEGER)''') | |
| # Load image data from the folder | |
| dataset_path = os.path.join(os.getcwd(), 'content/nuforc_reports') | |
| dataset = DatasetDict.from_disk(dataset_path) | |
| image_files = [example['file'] for example in dataset['train']] | |
| # Function to vote for an image | |
| def vote_for_image(filename, vote): | |
| if vote == 'UAP': | |
| c.execute("UPDATE votes SET uap_votes = uap_votes + 1 WHERE filename = ?", (filename,)) | |
| elif vote == 'Not UAP': | |
| c.execute("UPDATE votes SET not_uap_votes = not_uap_votes + 1 WHERE filename = ?", (filename,)) | |
| conn.commit() | |
| # Get vote counts for an image | |
| def get_vote_counts(filename): | |
| c.execute("SELECT uap_votes, not_uap_votes FROM votes WHERE filename = ?", (filename,)) | |
| row = c.fetchone() | |
| if row: | |
| return row | |
| else: | |
| c.execute("INSERT INTO votes (filename, uap_votes, not_uap_votes) VALUES (?, 0, 0)", (filename,)) | |
| conn.commit() | |
| return (0, 0) | |
| # Gradio interface | |
| image_select = gr.Dropdown(image_files, label="Select an image") | |
| votes = gr.RenderedHTML() | |
| with gr.Blocks() as demo: | |
| with gr.Row(): | |
| with gr.Column(): | |
| image = gr.Image(value=f"{dataset_path}/{image_files[0]}", shape=(400, 400)) | |
| with gr.Column(): | |
| uap_vote = gr.Button("UAP") | |
| not_uap_vote = gr.Button("Not UAP") | |
| image_select.change(lambda x: f"{dataset_path}/{x}", inputs=image_select, outputs=image) | |
| uap_vote.click(vote_for_image, inputs=[image_select, gr.Const("UAP")], outputs=None) | |
| not_uap_vote.click(vote_for_image, inputs=[image_select, gr.Const("Not UAP")], outputs=None) | |
| vote_counts = gr.Column() | |
| image_select.change(lambda x: gr.Markdown(f"**UAP votes**: {get_vote_counts(x)[0]}\n**Not UAP votes**: {get_vote_counts(x)[1]}"), inputs=image_select, outputs=vote_counts) | |
| demo.launch() |