Dataset1 Image Dataset

2024-06-29 9:53pm

2024-06-19 8:40pm

2024-06-12 9:07pm

2024-06-10 1:28pm

2024-01-29 4:31am

2024-01-25 5:30am

2024-01-19 3:36am

2023-11-10 6:44pm

2023-11-08 7:41pm

2023-11-08 7:16pm

2023-11-08 6:10pm

2023-11-08 5:01pm

2023-11-07 8:03pm

2023-11-07 7:44pm

2023-11-07 7:42pm

2023-11-07 7:37pm

2023-11-07 7:14pm

2023-11-07 7:09pm

2023-11-03 3:44pm

2023-11-03 3:34pm

2023-11-03 3:28pm

2023-11-03 3:22pm

2023-11-03 3:16pm

2023-11-02 5:56pm

2023-11-02 5:21pm

2023-11-02 5:11pm

2023-11-02 8:52am

2023-11-02 8:48am

2023-11-02 8:41am

2023-11-02 8:34am

2023-11-02 8:29am

2023-11-02 8:22am

2023-11-01 8:12pm

2023-11-01 8:02pm

2023-11-01 7:42pm

2023-10-31 6:23pm

2023-10-31 6:05pm

2023-10-31 5:45pm

2023-10-27 2:13pm

2023-10-27 11:21am

2023-10-27 11:16am

2023-10-27 11:12am

2023-10-27 11:02am

2023-10-27 10:49am

2023-10-27 10:40am

2023-10-26 8:58am

2023-10-26 8:36am

2023-10-26 8:31am

2023-10-26 8:20am

2023-10-25 8:53pm

2023-10-25 8:43pm

2023-10-25 8:17pm

2023-10-25 8:13pm

2023-10-25 8:11pm

2023-10-25 8:02pm

2023-10-20 9:39pm

2023-10-20 9:19pm

2023-10-20 7:20pm

2023-10-20 7:13pm

2023-10-20 6:50pm

2023-10-20 6:44pm

2023-10-19 6:24pm

2023-10-19 6:11pm

2023-10-19 6:07pm

2023-10-19 5:59pm

2023-10-19 5:53pm

2023-10-19 5:48pm

2023-10-19 5:21pm

2023-10-19 5:14pm

2023-10-19 9:05am

2023-10-19 8:44am

2023-10-19 8:36am

2023-10-14 4:39pm

2023-10-14 4:22pm

2023-10-14 4:19pm

2023-10-13 8:56pm

2023-10-13 8:48pm

2023-10-13 8:44pm

2023-10-13 8:41pm

2023-10-13 8:32pm

2023-10-13 8:27pm

2023-10-13 8:24pm

2023-10-13 8:19pm

2023-10-13 8:16pm

2023-10-13 8:14pm

2023-10-13 7:08pm

2023-10-13 7:03pm

2023-10-13 6:57pm

2023-10-13 6:51pm

2023-10-13 6:40pm

2023-10-13 6:18pm

2023-10-13 6:13pm

2023-10-13 6:06pm

2023-10-12 5:15pm

2023-10-12 5:07pm

2023-10-12 4:33pm

2023-10-12 4:18pm

2023-10-07 1:33pm

2023-10-07 1:16pm

2023-10-07 12:53pm

2023-10-07 12:42pm

2023-10-07 12:34pm

2023-10-07 12:01pm

2023-10-07 11:45am

2023-10-07 11:41am

2023-10-07 11:06am

2023-10-01 3:03pm

v109

2024-06-29 9:53pm

Generated on Jun 29, 2024

Download Dataset

Popular Download Formats

TXT annotations and YAML config used with YOLOv9.

TXT annotations and YAML config used with YOLOv8.

TXT annotations and YAML config used with YOLOv5.

TXT annotations and YAML config used with YOLOv7.

COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.

Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.

Common XML annotation format for local data munging (pioneered by ImageNet).

TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.

PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.

CreateML JSON format is used with Apple's CreateML and Turi Create tools.

Choose another format.

726 Total Images

View All Images

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Annotation Visualization

Dataset Split

Train Set 100%

726Images

Valid Set %

0Images

Test Set %

0Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x640

Augmentations

No augmentations were applied.

Similar Projects

More like archangel-xrku5/dataset1-u6xs8

-person--hYXV

726 images

Object Detection

Human Detection

human

771 images

Object Detection Model snap

vehicles-humans-livestock

2286 images

Object Detection

Damage Detection

Saitama university

DL1, DL2,DL3,DL4,DL5

79 images

Object Detection

earthquake-cities

295 images

Classification Model