Primary competition visual

Local Ocean Conservation Sea Turtle Face Detection

Helping Kenya
Knowledge
Active
Object Detection
Computer Vision
424 joined
84 active
About

Data for this competition consists of images along with bounding box annotations. The images are available in multiple sizes. Filenames take the form Image_ID.JPG. Train.csv contains the Image_IDs and bounding box annotations for the training set. SampleSubmission.csv shows the submission format and contains the Image_IDs of the test set.

Bounding boxes are rectangles defined by four numbers: x, y, w (width) and h (height). The rectangle spans from x to (x+w), and from y to (y+h). These numbers are floats (fractions of the image dimensions in pixels). The starter notebook shows how to convert these to pixel locations whatever the input image size is.

Wildbook and Wildbook-IA code are open source and free to use. Here is the link to Wildbook-IA on our github: https://github.com/WildbookOrg/wildbook-ia. You can use this as a starting point.

Files
Description
Files
Train contains the target. This is the dataset that you will use to train your model.
This file contains all images resized to 512 px.
This file contains all images resized to 1024 px.
This notebook will help you make your first submission to the leaderboard.
This shows the submission format for this competition, with the ‘ID’ column mirroring that of Test.csv and the ‘target’ column containing your predictions. The order of the rows does not matter, but the names of the ID must be correct.