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doors
Object Detection
Overview
Images
2896
Dataset
68
Model
64
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Dataset Versions
Try Pre-Trained Model
Versions
YOLO11 ADAM 0.001 SMALL
v68
·
2 months ago
YOLO8 ADAMW 0.001 SMALL
v67
·
2 months ago
DOOR YOLO 11 ADAMW 0.001 SMALL
v66
·
2 months ago
DOOR YOLO 11 ADAM 0.001 SMALL
v65
·
2 months ago
DOOR YOLO 11 SGD 0.001 SMALL
v64
·
2 months ago
DOOR YOLO 11 SGD 0.001-2-
v63
·
2 months ago
DOOR YOLO 11 ADAM 0.01-2-
v62
·
2 months ago
DOOR YOLO 11 ADAMW 0.1 -2-
v61
·
2 months ago
DOOR YOLO 11 ADAM 0.1 -2-
v60
·
2 months ago
DOOR YOLO 11 SGD 0.1 -2-
v59
·
2 months ago
DOOR YOLO 11 ADAMW 0.1 SMALL-2-
v58
·
2 months ago
DOOR YOLO 8 ADAMW 0.1 -2-
v57
·
2 months ago
DOOR YOLO 11 ADAM 0.01 SMALL
v56
·
3 months ago
DOOR YOLO 11 ADAMW 0.01 SMALL
v55
·
3 months ago
DOOR YOLO 11 SGD 0.01 SMALL
v54
·
3 months ago
DOOR YOLO 11 ADAMW 0.1 SMALL
v53
·
3 months ago
DOOR YOLO 8 SGD 0.1
v52
·
3 months ago
DOOR YOLO 8 SGD 0.1 NANO
v51
·
3 months ago
DOOR YOLO 8 ADAM 0.1 NANO
v50
·
3 months ago
DOOR YOLO8 ADAMW 0.1 NANO
v49
·
3 months ago
DOOR YOLO 8 SGD 0.1
v48
·
3 months ago
DOOR YOLO 8 ADAM 0.1
v47
·
3 months ago
DOOR YOLO 8 ADAMW 0.1
v46
·
3 months ago
DOOR YOLO 8 SGD 0.01 NANO
v45
·
3 months ago
DOOR YOLO 8 ADAM 0.01 NANO
v44
·
3 months ago
DOOR YOLO 8 ADAMW 0.01 NANO
v43
·
3 months ago
DOOR YOLO 8 SGD 0.01
v42
·
3 months ago
DOOR YOLO 8 ADAM 0.01
v41
·
3 months ago
WITH BLUR
v40
·
3 months ago
DOOR YOLO 8 SGD 0.001 NANO
v39
·
3 months ago
DOOR YOLO 8 ADAM 0.001 NANO
v38
·
3 months ago
DOOR YOLO 8 ADAMW 0.001 NANO
v37
·
3 months ago
DOOR YOLO 8 SGD 0.001
v36
·
3 months ago
DOOR YOLO 8 ADAM 0.001
v35
·
3 months ago
DOOR YOLO8 ADAMW 0.01
v34
·
3 months ago
DOOR YOLO8 ADAMW 0.001
v33
·
3 months ago
DOOR YOLO 11 ADAM0.1 SMALL
v32
·
3 months ago
DOOR YOLO 11 SGD0.1 SMALL
v31
·
3 months ago
DOOR YOLO 11 ADAMW 0.001
v30
·
3 months ago
DOOR YOLO 11 ADAM 0.001
v29
·
3 months ago
DOOR YOLO 11 SGD 0.001
v28
·
3 months ago
DOOR YOLO 11 ADAMW 0.01
v27
·
3 months ago
DOOR YOLO 11 ADAM 0.01
v26
·
3 months ago
DOOR YOLO 11 SGD 0.01
v25
·
3 months ago
DOOR YOLO 11 ADAMW 0.1
v24
·
3 months ago
DOOR YOLO 11 ADAM 0.1
v23
·
3 months ago
DOOR YOLO 11 SGD 0.1
v22
·
3 months ago
2024-09-09 5:46pm
v21
·
5 months ago
Dufalt 100
v20
·
5 months ago
Dufalt 50
v19
·
5 months ago
DSgd 0.01 50 5
v18
·
5 months ago
DAdamw 0.001 100 5
v17
·
5 months ago
DSgd 0.1 50 5
v16
·
5 months ago
DAdamw 0.01 5 100
v15
·
5 months ago
DAdamw 0.1 100 5
v14
·
5 months ago
DAdamw 0.001 50 5
v13
·
5 months ago
DAdamw 0.01 5 50
v12
·
5 months ago
DAdamW 0.1 50 5
v11
·
5 months ago
DAdam 0.001 100 5
v10
·
5 months ago
DAdam 0.01 5 100
v9
·
5 months ago
DAdam 0.1 100 5
v8
·
5 months ago
DAdam 0.01 5 50
v7
·
5 months ago
100 adam 0.001
v6
·
5 months ago
100 sgd 0.001 5
v5
·
5 months ago
100 Adam 0.001 5
v4
·
6 months ago
DAdam 0.1 50 5
v3
·
6 months ago
DAdam 0.001 50 5
v2
·
6 months ago
2024-08-16 7:34pm
v1
·
6 months ago
v39
DOOR YOLO 8 SGD 0.001 NANO
Generated on Nov 10, 2024
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.
2896
Total Images
View All Images
Dataset Split
Train Set
70%
2031
Images
Valid Set
20%
579
Images
Test Set
10%
286
Images
Preprocessing
No preprocessing steps were applied.
Augmentations
No augmentations were applied.
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