| # Heinken |
|
|
| > Heineken-themed frame and SKU vision datasets. |
|
|
| ## At a Glance |
| | Metric | Value | |
| | --- | --- | |
| | Archives | 2 | |
| | Total images | 66 | |
| | Primary format | Roboflow-style YOLO vision export | |
| | Delivery format | Zip archives inside each folder | |
|
|
| ## Archive Inventory |
| | Archive | Images | Classes | Project | Source | |
| | --- | ---: | ---: | --- | --- | |
| | `HEINKEN FRAME.zip` | 33 | 1 | `heineken_frame` | [dataset](https://universe.roboflow.com/gp-project-i3bp5/heineken_frame/dataset/3) | |
| | `HEINKEN SKU.zip` | 33 | 22 | `heineken-l93wc` | [dataset](https://universe.roboflow.com/gp-project-i3bp5/heineken-l93wc/dataset/7) | |
|
|
| ## Folder Layout |
| ```text |
| archive.zip |
| +-- data.yaml |
| +-- train/ |
| | +-- images/ |
| | +-- labels/ |
| +-- valid/ or val/ |
| +-- test/ |
| ``` |
|
|
| ## Working With the Data |
| 1. Extract the archive you want to inspect. |
| 2. Open `data.yaml` to confirm class names and split locations. |
| 3. Use the image and label pairs directly for YOLO training, validation, or audit workflows. |
|
|
| ## Notes |
| - These archives follow a Roboflow export pattern and keep the original `data.yaml` metadata inside each zip. |
| - Several folders contain multiple related datasets; the table above lists each archive separately. |
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