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football-team-separation/35 (latest)
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Football Team separation
Object Detection
Overview
Images
2428
Dataset
28
Model
7
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
2023-12-01 10:04am
v35
·
a year ago
2023-11-25 7:19pm
v34
·
a year ago
2023-11-20 1:19pm
v33
·
a year ago
2023-11-15 3:22pm
v32
·
a year ago
2023-10-26 11:38am
v31
·
a year ago
2023-10-17 1:56pm
v30
·
a year ago
2023-10-17 12:35pm
v29
·
a year ago
2023-10-17 12:33pm
v28
·
a year ago
2023-10-17 12:26pm
v26
·
a year ago
2023-09-07 4:22pm
v25
·
2 years ago
2023-06-26 12:46pm
v24
·
2 years ago
2023-06-26 12:14pm
v23
·
2 years ago
2023-05-18 12:02am
v22
·
2 years ago
2023-05-15 12:06pm
v21
·
2 years ago
2023-04-25 7:01pm
v20
·
2 years ago
2023-04-20 12:46pm
v18
·
2 years ago
2023-03-24 12:17pm
v15
·
2 years ago
2023-03-24 1:41am
v14
·
2 years ago
2023-03-21 1:05pm
v13
·
2 years ago
2023-03-20 12:39pm
v12
·
2 years ago
2023-02-27 4:38pm
v11
·
2 years ago
2023-02-27 1:40pm
v10
·
2 years ago
2023-02-21 9:23pm
v5
·
2 years ago
2023-02-21 5:39pm
v4
·
2 years ago
2023-02-21 8:52am
v3
·
2 years ago
2023-02-20 6:10pm
v2
·
2 years ago
2023-02-20 6:04pm
v1
·
2 years ago
v21
2023-05-15 12:06pm
Generated on May 15, 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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2589
Total Images
View All Images
Dataset Split
Train Set
88%
2289
Images
Valid Set
8%
201
Images
Test Set
4%
99
Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 1280x720
Modify Classes:
10 remapped, 5 dropped
Augmentations
Outputs per training example:
3
Brightness:
Between -25% and +25%
Noise:
Up to 5% of pixels
Bounding Box: Brightness:
Between -25% and +25%
Bounding Box: Blur:
Up to 10px
Bounding Box: Noise:
Up to 12% of pixels
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