Dataset Versions

2023-04-20 10:46am

Generated on Apr 20, 2023

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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.

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1600 Total Images

View All Images

Dataset Split

Train Set 70%

1115Images

Valid Set 20%

317Images

Test Set 11%

168Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x640

Auto-Adjust Contrast: Using Adaptive Equalization

Augmentations

No augmentations were applied.

Similar Projects

Annotations

Group:

vegetation

CLASSES

LAYERS

vegetation

16789-83-16789-1720220523.jpg

640x640

0.41MP

Updated Apr 20, 2023

1:46AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Resize	Stretch to 640x640
Auto-Adjust Contrast	Adaptive Equalization

Raw Data

{
    "camera": "Generated by Roboflow",
    "classes": {
        "vegetation": 4512
    },
    "datasets": [
        "AsRQVyfln9n3klfSg05L"
    ],
    "destination": "48c38b2d92a094dd0abd89b184809130",
    "height": 640,
    "id": "Xqeot18EfQvdtpu3hNzp",
    "label": [],
    "labels": [],
    "name": "16789-83-16789-1720220523.jpg",
    "numSteps": 3,
    "owner": "giJnNsEF2mudIm8SeoUa",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",640,640]",
        "auto-contrast:[\"Adaptive Equalization\"]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 640x640"
        },
        {
            "name": "Auto-Adjust Contrast",
            "value": "Adaptive Equalization"
        }
    ],
    "source": "Xqeot18EfQvdtpu3hNzp",
    "split": "train",
    "split.AsRQVyfln9n3klfSg05L.5": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,640]\",\n    \"auto-contrast:[\\\"Adaptive Equalization\\\"]\"\n]",
    "updated": {
        "_seconds": 1681955205,
        "_nanoseconds": 842000000
    },
    "updatedDate": "Apr 20, 2023",
    "updatedTime": "1:46AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "AsRQVyfln9n3klfSg05L/5"
    ],
    "width": 640
}

{
    "boxes": [
        {
            "label": "vegetation",
            "x": 168,
            "y": 324,
            "width": 184,
            "height": 477.5
        },
        {
            "label": "vegetation",
            "x": 45.5,
            "y": 477,
            "width": 60.5,
            "height": 152
        },
        {
            "label": "vegetation",
            "x": 431.5,
            "y": 209,
            "width": 94.5,
            "height": 135.5
        }
    ],
    "height": 640,
    "key": "16789-83-16789-1720220523.jpg",
    "width": 640
}

Vegetation Detection