Trash Detection Dataset annotation - UAV dataset Image Dataset
Versions
V4 - Haider Annotation is included - Previous Augmentation only
v22
Oct 20, 2023
V3.1 - Faizan images is updated- Previous Accepted Augmentation is applied
v21
Oct 19, 2023
V2.1.3 - Appropriate augmentation is selected
v20
Oct 19, 2023
mosaic augmentation is applied- but left it for now
v19
Oct 19, 2023
2023-10-20 12:12am
v18
Oct 19, 2023
2023-10-19 11:54pm
v17
Oct 19, 2023
2023-10-19 11:42pm
v16
Oct 19, 2023
2023-10-19 11:39pm
v15
Oct 19, 2023
2023-10-19 11:37pm
v14
Oct 19, 2023
2023-10-19 11:27pm
v13
Oct 19, 2023
2023-10-19 11:24pm
v12
Oct 19, 2023
2023-10-19 10:16pm
v10
Oct 19, 2023
V2.1.2 - Ashar Images and original Images_ Multiple Augmentations tryout
v9
Oct 19, 2023
V2.1 - Ashar Images and original Images_ no Augment
v8
Oct 19, 2023
V2 - Original annotation only__Augmentation Applied 3x
v7
Oct 19, 2023
V1 - Original Annotation is remapped to TRASH
v6
Oct 19, 2023
V0 - Before Custom Annotation
v4
Oct 18, 2023
2023-10-18 8:10pm
v2
Oct 18, 2023
v22
V4 - Haider Annotation is included - Previous Augmentation only
Generated on Oct 20, 2023
Popular Download Formats
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
402 Total Images
View All Images
Dataset Split
Train Set 100%
402Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Modify Classes: 1 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Grayscale: Apply to 8% of images
Noise: Up to 2% of pixels
Cutout: 13 boxes with 1% size each
Bounding Box: Flip: Vertical
Bounding Box: Brightness: Between -15% and +15%
Bounding Box: Exposure: Between -40% and +40%
plastic-waste
40 images
plastic-debris-wood
25 images
littter-9y3t
216 images
detecting-marine-debris
90 images
plasticDA
1327 images