Datasets:
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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We construct the dataset by scraping user-generated prompts from the Midjourney Discord server.
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The server contains channels in which a user can type a prompt and arguments, and then the Midjourney bot would reply with 4 generated images, combined together into a grid. Then, if the user is satisfied with one of the 4 images, they can send an
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We randomly choose one of the
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#### Data Collection and Processing
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<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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We construct the dataset by scraping user-generated prompts from the Midjourney Discord server.
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The server contains channels in which a user can type a prompt and arguments, and then the Midjourney bot would reply with 4 generated images, combined together into a grid. Then, if the user is satisfied with one of the 4 images, they can send an 'upscale' command to the bot, to get an upscaled version of the desired image.
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We randomly choose one of the 'newbies' channels, where both new and experienced users are experimenting with general domain prompts. We collect $693,528$ prompts (From 23 January to 1 March 2023), together with their matching images and meta-data such as timestamps and user ids (which we anonymize).
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#### Data Collection and Processing
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