Underwater Seafloor Litter Drone Image Database
Original RAW
These are the original images captured with drones: DJI Mavic pro 2 camera Hasselblad 20MP 4K UHD
and DJI air 2S camera 2.4. µm 5.4K UHD.
| Key | Value |
|---|---|
| Number of images | 5 405 |
| Number of labels | 12 786 |
| Size | ~193 GB |
| Format | DNG |
| Resolution | 5568 x 3648, 5568 x 3078, 5472 x 3648 |
| Classes | 31 (Fragments, Constructional material, Tires, Cans, Bottles, Ropes, Cloth, Bags, Fishing tools, Caps & lids, Cups, Buckets, Pipe, Footwear, Cartons, Dishes, Paper, Chain, Chair, Shopping carts, Trash can, Road sign, Dumpster, Boats, Glove, Car parts, Traffic cone, Flipper, Scooter, Electric drill, Cigarette butt) |
| Format | COCO, Voxel51 |
| Preview | No preview available |
Half Size
Dataset that has been halved in width and height and converted to PNG for faster manipulation. All
other datasets stem from this one.
| Key | Value |
|---|---|
| Number of images | 5 405 |
| Number of labels | 12 786 |
| Size | ~33 GB |
| Format | PNG |
| Resolution | 2732 x 1820, 2732 x 1535 |
| Classes | 31 (Fragments, Constructional material, Tires, Cans, Bottles, Ropes, Cloth, Bags, Fishing tools, Caps & lids, Cups, Buckets, Pipe, Footwear, Cartons, Dishes, Paper, Chain, Chair, Shopping carts, Trash can, Road sign, Dumpster, Boats, Glove, Car parts, Traffic cone, Flipper, Scooter, Electric drill, Cigarette butt) |
| Format | COCO, Voxel51 |
| Preview | Note: Preview is in JPG format to speed up loading |
All Patches
Each annotation has been cropped to fit 640x640 size. For larger annotations scaling was used to fit
in 640x640. Nearby objects are all included in the same image, but same object might appear in
another image). Duplication was kept at minimum by only including something when it's not included
already. Some labels might be cropped if they cannot fit in the 640x640.
| Key | Value |
|---|---|
| Number of images | 6 298 |
| Number of labels | 17 913 |
| Size | 3.3 GB |
| Format | PNG |
| Resolution | 640 x 640 |
| Classes | 31 (Fragments, Constructional material, Tires, Cans, Bottles, Ropes, Cloth, Bags, Fishing tools, Caps & lids, Cups, Buckets, Pipe, Footwear, Cartons, Dishes, Paper, Chain, Chair, Shopping carts, Trash can, Road sign, Dumpster, Boats, Glove, Car parts, Traffic cone, Flipper, Scooter, Electric drill, Cigarette butt) |
| Format | COCO, Voxel51 |
| Preview | Note: Preview is in JPG format to speed up loading |
Selected Patches
Reduced and curated dataset of patches where only some of the classes are used (that can be properly
represented).
| Key | Value |
|---|---|
| Number of images | 4 016 |
| Number of labels | 10 958 |
| Size | 2.1 GB |
| Format | PNG |
| Resolution | 640 x 640 |
| Classes | 9 (Fragments, Construction material, Tires, Cans, Bottles, Cloth, Bags, Caps & lids, Cups) |
| Format | COCO, YOLO YAML (with train/val/test split) |
| Preview | Note: Preview is in JPG format to speed up loading |
