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README.md
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---
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pretty_name: BagBuddy Dataset
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size_categories:
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- n<1K
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task_categories:
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- image-classification
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- object-detection
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configs:
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- config_name: default
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data_files:
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- split: train
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path: "**/*"
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---
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# Yannik019/llm_pack_detection
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This repository contains the BagBuddy dataset as a raw folder upload.
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## Layout
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The root directory is organized into bucket folders such as `6`, `8`, `10`, and so on.
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Each bucket contains timestamped capture folders. Every capture folder is expected to
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contain:
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- `debug.jpg`
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- `view.jpg`
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- `depth.npy`
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- `groceries.json`
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The `groceries.json` file stores a list of labeled grocery items with at least the
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fields `name`, `idx`, `x`, and `y`.
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## Summary
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- Samples: 40
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- Total annotations: 520
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- Buckets: 8
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- Unique labels: 18
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### Samples Per Bucket
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- 10: 5 samples
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- 12: 5 samples
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- 14: 5 samples
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- 16: 5 samples
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- 18: 5 samples
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- 20: 5 samples
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- 6: 5 samples
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- 8: 5 samples
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### Label Frequencies
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- Joghurt Cup: 55
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- Energy Drink Can: 36
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- Noodles in Plastic Bag: 35
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- Bananas: 35
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- Strawberries: 33
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- Glass Beer Bottle: 32
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- Eggs: 32
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- Tomatoes: 31
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- Apples: 29
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- Onions: 29
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- 1.5L Plastic Water Bottle: 29
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- Mushrooms: 28
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- Canned Corn: 26
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- Lettuce: 22
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- Cucumber: 21
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- Bell Pepper: 19
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- Canned Beans: 18
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- Canned Peas: 10
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## Upload Notes
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This dataset was uploaded with `upload_dataset_to_huggingface.py`. Update this card
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if you want to document licensing, splits, or benchmark details more precisely.
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