Global Wheat Detection

Link : https://www.kaggle.com/competitions/global-wheat-detection/data

Dataset Description

 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.