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@@ -38,64 +38,34 @@ dataset_info:
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  dataset_size: 12169999
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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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-
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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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-
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- ## Upload Notes
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-
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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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