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vegetation-detection-mjmzp/1 (latest)
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Vegetation Detection
Object Detection
Overview
Images
1600
Dataset
5
Model
1
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
2023-04-20 10:46am
v5
·
2 years ago
2023-03-23 12:12pm
v4
·
2 years ago
2023-03-06 8:03am
v3
·
2 years ago
2023-03-06 7:43am
v2
·
2 years ago
2023-02-22 1:33am
v1
·
2 years ago
v1
2023-02-22 1:33am
Generated on Feb 21, 2023
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Dataset
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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
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478
Total Images
View All Images
Dataset Split
Train Set
87%
417
Images
Valid Set
8%
40
Images
Test Set
4%
21
Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 640x640
Auto-Adjust Contrast:
Using Adaptive Equalization
Augmentations
Outputs per training example:
3
Brightness:
Between -25% and +25%
Noise:
Up to 5% of pixels
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