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---
license: mit
task_categories:
- text-classification
- text-generation
language:
- en
tags:
- code
pretty_name: '*'
size_categories:
- 0.001M<n<0.0011M
---
# Modified Coco Dataset Files
# Required dependencies
```
OpenCV (cv2):
pip install opencv-python
```
# img_data.psv
Extract of the coco dataset containing the following labels: ```["airplane", "backpack", "cell phone", "handbag", "suitcase", "knife", "laptop", "car"]```
```
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.
# display_boundary.py
Mini gui for viewing images with their boundary boxes, don't need to pay attention to how it works, just do the following:
Ensure you're in the same working directory as display_boundary.py
```
cd mini_coco_dataset
```
```
python display_boundary.py
```
- It takes an image name as input (x.png), to find image names look in the data folder.
If you have any questions or issues, feel free to keep them to yourself. |