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authentic-neozep-forte/4 (latest)
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Authentic Neozep Forte
Object Detection
Overview
Images
112
Dataset
6
Model
1
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
2024-01-06 11:03pm
v10
·
a year ago
2024-01-06 11:02pm
v9
·
a year ago
2024-01-06 11:01pm
v8
·
a year ago
2024-01-06 10:55pm
v7
·
a year ago
2023-11-29 2:30pm
v4
·
a year ago
2023-11-29 10:00am
v1
·
a year ago
v7
2024-01-06 10:55pm
Generated on Jan 6, 2024
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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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270
Total Images
View All Images
Dataset Split
Train Set
88%
237
Images
Valid Set
8%
22
Images
Test Set
4%
11
Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example:
3
90° Rotate:
Clockwise, Counter-Clockwise, Upside Down
Crop:
0% Minimum Zoom, 20% Maximum Zoom
Rotation:
Between -15° and +15°
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