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README.md
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dataset_size: 12169999
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#
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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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fields `name`, `idx`, `x`, and `y`.
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- Unique labels: 18
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### Samples Per Bucket
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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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dataset_size: 12169999
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---
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# BagBuddy HF Dataset Export
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## Files
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- `train.parquet`: self-contained parquet export with embedded image bytes
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- `dataset_info.json`: metadata produced by the `datasets` library
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- `saved_dataset/`: optional `save_to_disk` export for local reloading
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## Schema
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- `image`: the `view.jpg` scene image
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- `caption`: generated caption summarizing the scene labels
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- `bucket`: top-level source bucket directory such as `6` or `10`
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- `sample_id`: timestamped sample folder name
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- `labels`: grocery item labels from `groceries.json`
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- `annotation_indices`, `annotation_x`, `annotation_y`: annotation metadata
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- `annotation_count`: number of annotated items in the scene
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## Hub Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset("Yannik019/llm_pack_detection", split="train")
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print(dataset)
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```
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## Row count
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- Rows: 40
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