Spaces:
Running
Running
| Dataset Description | |
| In this competition you will be using geostationary satellite images to identify aviation contrails. The original satellite images were obtained from the GOES-16 Advanced Baseline Imager (ABI), which is publicly available on Google Cloud Storage. The original full-disk images were reprojected using bilinear resampling to generate a local scene image. Because contrails are easier to identify with temporal context, a sequence of images at 10-minute intervals are provided. Each example (record_id) contains exactly one labeled frame. | |
| Learn more about the dataset from the preprint: OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI. Labeling instructions can be found at in this supplementary material. Some key labeling guidance: | |
| Contrails must contain at least 10 pixels | |
| At some time in their life, Contrails must be at least 3x longer than they are wide | |
| Contrails must either appear suddenly or enter from the sides of the image | |
| Contrails should be visible in at least two image | |
| Ground truth was determined by (generally) 4+ different labelers annotating each image. Pixels were considered a contrail when >50% of the labelers annotated it as such. Individual annotations (human_individual_masks.npy) as well as the aggregated ground truth annotations (human_pixel_masks.npy) are included in the training data. The validation data only includes the aggregated ground truth annotations. | |
| Files | |
| train/ - the training set; each folder represents a record_id and contains the following data: | |
| band_{08-16}.npy: array with size of H x W x T, where T = n_times_before + n_times_after + 1, representing the number of images in the sequence. There are n_times_before and n_times_after images before and after the labeled frame respectively. In our dataset all examples have n_times_before=4 and n_times_after=3. Each band represents an infrared channel at different wavelengths and is converted to brightness temperatures based on the calibration parameters. The number in the filename corresponds to the GOES-16 ABI band number. Details of the ABI bands can be found here. | |
| human_individual_masks.npy: array with size of H x W x 1 x R. Each example is labeled by R individual human labelers. R is not the same for all samples. The labeled masks have value either 0 or 1 and correspond to the (n_times_before+1)-th image in band_{08-16}.npy. They are available only in the training set. | |
| human_pixel_masks.npy: array with size of H x W x 1 containing the binary ground truth. A pixel is regarded as contrail pixel in evaluation if it is labeled as contrail by more than half of the labelers. | |
| validation/ - the same as the training set, without the individual label annotations; it is permitted to use this as training data if desired | |
| test/ - the test set; your objective is to identify contrails found in these records. | |
| {train|validation}_metadata.json - metadata information for each record; contains the timestamps and the projection parameters to reproduce the satellite images. | |
| sample_submission.csv - a sample submission file in the correct format |