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citrus-leaves-diseases-ykhpu/3 (latest)
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citrus leaves diseases
Object Detection
Overview
Images
1250
Dataset
4
Model
1
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
romm
v6
·
2 years ago
HueSaturationExposureBlur
v5
·
2 years ago
SSD
v3
·
2 years ago
2023-07-18 6:13pm
v1
·
2 years ago
v5
HueSaturationExposureBlur
Generated on Jul 26, 2023
Download
Dataset
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.
3150
Total Images
View All Images
Dataset Split
Train Set
90%
2850
Images
Valid Set
5%
147
Images
Test Set
5%
153
Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 640x640
Augmentations
Outputs per training example:
3
Hue:
Between -35° and +35°
Saturation:
Between -40% and +40%
Exposure:
Between -15% and +15%
Blur:
Up to 2px
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