More details on the data acquisition and processes are available at https://arxiv.org/abs/2005.02162

## What should I expect the data format to be?

The data is images of wheat fields, with bounding boxes for each identified wheat head. Not all images include wheat heads / bounding boxes. The images were recorded in many locations around the world.

The CSV data is simple - the image ID matches up with the filename of a given image, and the width and height of the image are included, along with a bounding box (see below). There is a row in `train.csv` for each bounding box. Not all images have bounding boxes.

Most of the test set images are hidden. A small subset of test images has been included for your use in writing code.

## What am I predicting?

You are attempting to predict bounding boxes around each wheat head in images that have them. If there are no wheat heads, you must predict no bounding boxes.

## Files

*   **train.csv** - the training data
*   **sample_submission.csv** - a sample submission file in the correct format
*   **train.zip** - training images
*   **test.zip** - test images

## Columns

*   `image_id` - the unique image ID
*   `width`, `height` - the width and height of the images
*   `bbox` - a bounding box, formatted as a Python-style list of [xmin, ymin, width, height]
*   etc.