Table 2 Details of the TrashBox dataset.
From: Enhancing trash classification in smart cities using federated deep learning
Trash classes | Sub-classes | No. of images | Total |
|---|---|---|---|
Cardboard | Assorted cardboard objects | 2414 | 2414 |
E-waste | Electric wires | 568 | 2883 |
Laptops and smartphones | 774 | ||
Small appliances | 926 | ||
Electrical chips | 615 | ||
Metal | Beverage cans | 1000 | 2586 |
Construction scrap | 539 | ||
Spray cans | 500 | ||
Metal containers | 505 | ||
Miscellaneous metal | 42 | ||
Plastic | Plastic bags | 504 | 2669 |
Plastic bottles | 571 | ||
Plastic containers | 580 | ||
Plastic cups | 507 | ||
Cigarette butts | 507 | ||
Paper | Tetra pak | 794 | 2695 |
News paper | 200 | ||
Paper cups | 639 | ||
Other paper objects | 1062 | ||
Glass | Assorted glass objects | 2528 | 2528 |
