| --- |
| license: mit |
| task_categories: |
| - text-classification |
| - text-generation |
| language: |
| - en |
| tags: |
| - code |
| pretty_name: '*' |
| size_categories: |
| - 0.001M<n<0.0011M |
| --- |
| |
| # mini coco dataset files |
|
|
| # Required dependencies |
|
|
| ``` |
| OpenCV (cv2) |
| |
| matplotlib |
| |
| ipywidgets |
| ``` |
|
|
|
|
| # img_data.psv |
| |
| Extract of the coco dataset containing the following labels: ```["airplane", "backpack", "cell phone", "handbag", "suitcase", "knife", "laptop", "car"]``` (300 of each) |
| |
| ``` |
| Structured as follows: |
| |
| | Field | Description | |
| | --------------- | --------------------------------------------------------------------------------------------------- | |
| | file_name | Name of image file (.png) | |
| | height | Image height prior to padding | |
| | width | Image width prior to padding | |
| | annotations | Array of boundary box array, label pairs. Bbox arrays are of the form [x_min, y_min, width, height] | |
|
|
| 1.09k rows |
| ``` |
| |
| |
| # /data (folder) |
| |
| This directory contains a selection of zero-padded COCO images that correspond to img_data.parquet, image names are of the following format: |
| ``` |
| xxxxxx.png |
| ``` |
| |
| |
| # display_boundary.py |
| |
| Allows images to be viewed with their boundary boxes, don't need to pay attention to how it works. |
| |
| ``` |
| - Intended to run in tandem with jupyter notebook. |
|
|
| - Takes img_name.png as input, inspect img_data.psv or /data for image names. |
|
|
| ``` |
| |
| |
| If you have any questions or issues, feel free to keep them to yourself. |
