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malaysian-food-recognition-2-0kwwr/7 (latest)
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Malaysian Food Recognition 2
Object Detection
Overview
Images
757
Dataset
7
Model
6
API Docs
Analytics
Dataset Versions
Try Pre-Trained Model
Versions
2024-11-08 3:27am
v7
·
4 months ago
2024-10-27 3:39pm
v6
·
5 months ago
2024-10-27 3:11pm
v5
·
5 months ago
2024-09-23 5:15am
v4
·
6 months ago
2024-09-01 3:12am
v3
·
7 months ago
2024-08-31 4:33pm
v2
·
7 months ago
2024-08-29 1:07pm
v1
·
7 months ago
v7
2024-11-08 3:27am
Generated on Nov 8, 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
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Tensorflow 2.0 Object Detection
models.
PaliGemma
PaliGemma JSONL format
used for fine-tuning
PaliGemma
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CreateML JSON
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1819
Total Images
View All Images
Dataset Split
Train Set
88%
1593
Images
Valid Set
8%
150
Images
Test Set
4%
76
Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 320x320
Auto-Adjust Contrast:
Using Histogram Equalization
Augmentations
Outputs per training example:
3
Flip:
Horizontal, Vertical
Crop:
0% Minimum Zoom, 30% Maximum Zoom
Hue:
Between -17° and +17°
Saturation:
Between -27% and +27%
Exposure:
Between -15% and +15%
Noise:
Up to 0.89% of pixels
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