Datasets:
Andy Janco
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README.md
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- [Зрелища](https://figgy.princeton.edu/concern/scanned_resources/1af8b322-a0b1-46af-8541-5c3054af8098/manifest?manifest=https://figgy.princeton.edu/concern/scanned_resources/1af8b322-a0b1-46af-8541-5c3054af8098/manifest)
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'filename', 'dpul', 'journal', 'year', 'issue', 'uri', 'yolo', 'yolo_predictions', 'text', 'images_meta'
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- [Зрелища](https://figgy.princeton.edu/concern/scanned_resources/1af8b322-a0b1-46af-8541-5c3054af8098/manifest?manifest=https://figgy.princeton.edu/concern/scanned_resources/1af8b322-a0b1-46af-8541-5c3054af8098/manifest)
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## Model
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Using [makesense.ai](https://www.makesense.ai/) and a custom active learning application called ["Mayakovsky"](https://github.com/CDH-ITMO-Periodicals-Project/mayakovsky) we generated training data to add the new labels to a [YOLOv5 model](https://docs.ultralytics.com/tutorials/train-custom-datasets/).
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## Dataset
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With the trained and fine-tuned model, we generated predictions for each of the images in the collection. The dataset contains an entry for each image with the following fields:
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- filename, the
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'filename', 'dpul', 'journal', 'year', 'issue', 'uri', 'yolo', 'yolo_predictions', 'text', 'images_meta'
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