TRY THIS MODEL
Drop image here to test
robotdetection-znsey/1 (latest)
Versions
2024-01-30 10:09pm
v24
·
a year ago
2024-01-29 11:23am
v23
·
a year ago
2024-01-16 2:51pm
v22
·
a year ago
2023-12-16 4:31pm
v21
·
a year ago
2023-12-16 10:58am
v20
·
a year ago
2023-12-16 10:51am
v19
·
a year ago
2023-12-15 9:08pm
v18
·
a year ago
2023-12-15 7:53pm
v17
·
a year ago
2023-12-15 2:19pm
v16
·
a year ago
2023-12-12 11:34pm
v15
·
a year ago
2023-12-12 4:42pm
v14
·
a year ago
2023-12-12 4:33pm
v13
·
a year ago
2023-12-12 10:09am
v12
·
a year ago
2023-12-06 2:40pm
v11
·
a year ago
2023-11-30 4:34pm
v10
·
a year ago
2023-11-27 8:22pm
v9
·
a year ago
2023-11-27 8:07pm
v8
·
a year ago
2023-11-26 10:36am
v7
·
a year ago
2023-10-29 12:41pm
v6
·
a year ago
2023-10-27 6:17pm
v5
·
a year ago
2023-10-13 3:44pm
v4
·
a year ago
2023-10-09 3:39pm
v3
·
a year ago
2023-10-09 8:58am
v2
·
a year ago
2023-10-08 4:46pm
v1
·
a year ago
v6
2023-10-29 12:41pm
Generated on
Oct 29, 2023
Popular Download Formats
YOLOv11
TXT
annotations and YAML config used with YOLOv11.
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.
593 Total Images
View All Images
Dataset Split
Train
Set
88%
519Images
Valid
Set
8%
50Images
Test
Set
4%
24Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 160x160
Augmentations
Outputs per training example:
3
Flip:
Horizontal, Vertical
90° Rotate:
Clockwise, Counter-Clockwise
Crop:
0% Minimum Zoom, 39% Maximum Zoom
Rotation:
Between -3° and +3°
Shear:
±15° Horizontal, ±15° Vertical
Grayscale:
Apply to 25% of images
Hue:
Between -25° and +25°
Saturation:
Between -14% and +14%
Brightness:
Between -87% and +87%
Exposure:
Between -24% and +24%
Blur:
Up to 3.5px
Noise:
Up to 6% of pixels
Cutout:
3 boxes with 14% size each
Mosaic:
Applied
Similar Projects
See More
3543 images2 models
1299 images2 models
1913 images1 model
3737 images3 models
139 images