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Crop and Weed detection and classification using computer vision and deep learning models

Object Detection

Dataset Versions

Try Pre-Trained Model

2023-01-11 10:10pm

Generated on Jan 11, 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.

Other Formats

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2144 Total Images

View All Images

Dataset Split

Train Set 82%

1764Images

Valid Set 12%

253Images

Test Set 6%

127Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x640

Augmentations

Outputs per training example: 2

90° Rotate: Clockwise, Counter-Clockwise

Brightness: Between -25% and +25%

Similar Projects

Annotations

Group: crops-and-weed

Okra

Unused Classes

Bengal gram

Bermudagrass weed

Chrozophora weed

Cotton

Maize

Parthenium weed

Peanut

Sorghum

Velvetleaf weed

weed

Attributes

final-okra111.jpg

640x640

0.41MP

Updated Sep 7, 54999

10:08PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Resize	Stretch to 640x640
90° Rotate	Applied
Brightness	1%

Raw Data

{
    "camera": "Generated by Roboflow",
    "classes": {
        "Bengal gram": 247,
        "Bermudagrass weed": 210,
        "Chrozophora weed": 229,
        "Cotton": 149,
        "Maize": 96,
        "Okra": 142,
        "Parthenium weed": 237,
        "Peanut": 83,
        "Sorghum": 224,
        "Velvetleaf weed": 118,
        "weed": 469
    },
    "datasets": [
        "2gklo8mJU8nfYhrgCWIg"
    ],
    "destination": "9c180875c90c923a34a0ec27e066bc79",
    "height": 640,
    "id": "e6O930Fo5WPbh7QoWyD2",
    "label": [],
    "labels": [],
    "name": "final-okra111.jpg",
    "numSteps": 4,
    "owner": "gLpzTuGz8vfabDrV9pD5PO128DQ2",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",640,640]",
        "ninety:[90]",
        "brightness:[1]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 640x640"
        },
        {
            "name": "90° Rotate",
            "value": "Applied"
        },
        {
            "name": "Brightness",
            "value": "1%"
        }
    ],
    "source": "e6O930Fo5WPbh7QoWyD2",
    "split": "train",
    "split.2gklo8mJU8nfYhrgCWIg.1": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,640]\",\n    \"ninety:[90]\",\n    \"brightness:[1]\"\n]",
    "updated": 1673455241289,
    "updatedDate": "Sep 7, 54999",
    "updatedTime": "10:08PM",
    "updatedTimezone": "+00:00",
    "versions": [
        "2gklo8mJU8nfYhrgCWIg/1"
    ],
    "width": 640
}

{
    "boxes": [
        {
            "type": "polygon",
            "label": "Okra",
            "x": 263.75,
            "y": 341.25,
            "width": 37.5,
            "height": 67.5,
            "points": [
                [
                    245,
                    308.75
                ],
                [
                    245,
                    358.75
                ],
                [
                    257.5,
                    375
                ],
                [
                    271.25,
                    375
                ],
                [
                    282.5,
                    358.75
                ],
                [
                    276.25,
                    343.75
                ],
                [
                    277.5,
                    328.75
                ],
                [
                    253.75,
                    307.5
                ],
                [
                    245,
                    308.75
                ]
            ]
        },
        {
            "type": "polygon",
            "label": "Okra",
            "x": 368.75,
            "y": 373.125,
            "width": 162.5,
            "height": 146.25,
            "points": [
                [
                    306.25,
                    425
                ],
                [
                    322.5,
                    438.75
                ],
                [
                    341.25,
                    446.25
                ],
                [
                    371.25,
                    442.5
                ],
                [
                    380,
                    436.25
                ],
                [
                    381.25,
                    425
                ],
                [
                    361.25,
                    411.25
                ],
                [
                    382.5,
                    406.25
                ],
                [
                    423.75,
                    408.75
                ],
                [
                    430,
                    418.75
                ],
                [
                    432.5,
                    406.25
                ],
                [
                    450,
                    392.5
                ],
                [
                    445,
                    368.75
                ],
                [
                    426.25,
                    353.75
                ],
                [
                    410,
                    353.75
                ],
                [
                    390,
                    362.5
                ],
                [
                    387.5,
                    368.75
                ],
                [
                    395,
                    375
                ],
                [
                    376.25,
                    378.75
                ],
                [
                    373.75,
                    393.75
                ],
                [
                    352.5,
                    388.75
                ],
                [
                    350,
                    380
                ],
                [
                    366.25,
                    373.75
                ],
                [
                    380,
                    355
                ],
                [
                    405,
                    346.25
                ],
                [
                    417.5,
                    330
                ],
                [
                    387.5,
                    310
                ],
                [
                    351.25,
                    300
                ],
                [
                    332.5,
                    300
                ],
                [
                    296.25,
                    322.5
                ],
                [
                    296.25,
                    346.25
                ],
                [
                    303.75,
                    352.5
                ],
                [
                    312.5,
                    351.25
                ],
                [
                    312.5,
                    355
                ],
                [
                    305,
                    357.5
                ],
                [
                    302.5,
                    368.75
                ],
                [
                    290,
                    372.5
                ],
                [
                    287.5,
                    378.75
                ],
                [
                    317.5,
                    387.5
                ],
                [
                    326.25,
                    382.5
                ],
                [
                    326.25,
                    373.75
                ],
                [
                    331.25,
                    373.75
                ],
                [
                    333.75,
                    405
                ],
                [
                    308.75,
                    415
                ],
                [
                    306.25,
                    425
                ]
            ]
        }
    ],
    "height": 640,
    "key": "final okra111.jpg",
    "width": 640
}

Crop and Weed detection and classification using computer vision and deep learning models

Dataset Versions

2023-01-11 10:10pm

Popular Download Formats

2144 Total Images

Dataset Split

Preprocessing

Augmentations

Similar Projects

Annotations

Unused Classes

Attributes

final-okra111.jpg

Updated Sep 7, 54999

Generated by Roboflow

Training Set

Transforms

Annotation History

Raw Data