Edit Project

Malaysian Food Recognition 2

Object Detection

Dataset Versions

Try Pre-Trained Model

2024-11-08 3:27am

Generated on Nov 8, 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.

1819 Total Images

View All Images

Dataset Split

Train Set 88%

1593Images

Valid Set 8%

150Images

Test Set 4%

76Images

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

Similar Projects

Annotations

Group:

Malaysian-Dishes-x7R6-yF4X-PuQP

CLASSES

LAYERS

Roti-Canai

Unused Classes

Anchovies

Boiled-Egg

Char-Kuey-Teow

Chicken-Rendang

Curry-Puff

Fried-Chicken

Fried-Egg

Fried-Rice

Hokkien-Mee

Lo-Mein

Mee-Rebus

Mee-Siam

Peanuts

Rice

Sambal

Slices-Cucumber

42.jpg

320x320

0.10MP

Updated May 12, 56824

11:42AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Crop	Keep 80% Centered on 11%, 6%
Resize	Stretch to 320x320
Auto-Adjust Contrast	Histogram Equalization
Flip	Horizontal
Hue	16°
Saturation	-3%
Exposure	11%
Noise	0.17%

Raw Data

{
    "camera": "Generated by Roboflow",
    "classes": {
        "Anchovies": 190,
        "Boiled-Egg": 238,
        "Char-Kuey-Teow": 79,
        "Chicken-Rendang": 62,
        "Curry-Puff": 294,
        "Fried-Chicken": 76,
        "Fried-Egg": 56,
        "Fried-Rice": 80,
        "Hokkien-Mee": 62,
        "Lo-Mein": 109,
        "Mee-Rebus": 72,
        "Mee-Siam": 64,
        "Peanuts": 239,
        "Rice": 210,
        "Roti-Canai": 67,
        "Sambal": 191,
        "Slices-Cucumber": 196
    },
    "datasets": [
        "um49fhimM3Tnl1gAYlJQ"
    ],
    "destination": "ff5b536ecd932abc813cc2efa26022da",
    "height": 320,
    "id": "za30sSd9fglgWgsL2ChX",
    "label": [],
    "labels": [],
    "name": "42.jpg",
    "numSteps": 9,
    "owner": "nCQEN6ZZL0X5ygirm9YIAIw1GxR2",
    "preprocessing": [
        "auto-orient",
        "crop:[80,0.114566,0.057842]",
        "resize:[\"Stretch to\",320,320]",
        "auto-contrast:[\"Histogram Equalization\"]",
        "flip:[\"horizontal\"]",
        "hue:[16]",
        "saturation:[-3]",
        "exposure:[11]",
        "noise:[0.17,904268]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Crop",
            "value": "Keep 80%<br />Centered on 11%, 6%"
        },
        {
            "name": "Resize",
            "value": "Stretch to 320x320"
        },
        {
            "name": "Auto-Adjust Contrast",
            "value": "Histogram Equalization"
        },
        {
            "name": "Flip",
            "value": "Horizontal"
        },
        {
            "name": "Hue",
            "value": "16°"
        },
        {
            "name": "Saturation",
            "value": "-3%"
        },
        {
            "name": "Exposure",
            "value": "11%"
        },
        {
            "name": "Noise",
            "value": "0.17%"
        }
    ],
    "source": "za30sSd9fglgWgsL2ChX",
    "split": "train",
    "split.um49fhimM3Tnl1gAYlJQ.7": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"crop:[80,0.114566,0.057842]\",\n    \"resize:[\\\"Stretch to\\\",320,320]\",\n    \"auto-contrast:[\\\"Histogram Equalization\\\"]\",\n    \"flip:[\\\"horizontal\\\"]\",\n    \"hue:[16]\",\n    \"saturation:[-3]\",\n    \"exposure:[11]\",\n    \"noise:[0.17,904268]\"\n]",
    "updated": 1731036483751,
    "updatedDate": "May 12, 56824",
    "updatedTime": "11:42AM",
    "updatedTimezone": "+00:00",
    "user_tags": [
        "roti-canai"
    ],
    "versions": [
        "um49fhimM3Tnl1gAYlJQ/7"
    ],
    "width": 320
}

{
    "boxes": [
        {
            "type": "polygon",
            "label": "Roti-Canai",
            "x": 80,
            "y": 160,
            "width": 160,
            "height": 320,
            "points": [
                [
                    7.89916,
                    0
                ],
                [
                    3.529412,
                    28.493151
                ],
                [
                    0,
                    28.493151
                ],
                [
                    0,
                    28.839222
                ],
                [
                    4.705882,
                    30.684932
                ],
                [
                    30.588235,
                    56.986301
                ],
                [
                    38.823529,
                    81.09589
                ],
                [
                    40,
                    124.931507
                ],
                [
                    35.294118,
                    138.082192
                ],
                [
                    41.176471,
                    149.041096
                ],
                [
                    35.294118,
                    151.232877
                ],
                [
                    35.294118,
                    168.767123
                ],
                [
                    9.411765,
                    199.452055
                ],
                [
                    0,
                    220.493151
                ],
                [
                    0,
                    320
                ],
                [
                    132.54902,
                    320
                ],
                [
                    138.823529,
                    311.232877
                ],
                [
                    148.235294,
                    287.123288
                ],
                [
                    151.764706,
                    249.863014
                ],
                [
                    138.823529,
                    203.835616
                ],
                [
                    150.588235,
                    192.876712
                ],
                [
                    154.117647,
                    181.917808
                ],
                [
                    148.235294,
                    155.616438
                ],
                [
                    150.588235,
                    144.657534
                ],
                [
                    160,
                    144.657534
                ],
                [
                    158.823529,
                    107.39726
                ],
                [
                    149.411765,
                    78.90411
                ],
                [
                    124.705882,
                    37.260274
                ],
                [
                    105.882353,
                    21.917808
                ],
                [
                    82.352941,
                    24.109589
                ],
                [
                    62.941176,
                    0
                ],
                [
                    19.752322,
                    0
                ],
                [
                    15.294118,
                    39.452055
                ],
                [
                    7.058824,
                    30.684932
                ],
                [
                    13.647059,
                    0
                ],
                [
                    7.89916,
                    0
                ]
            ]
        }
    ],
    "height": 320,
    "key": "42.jpg",
    "width": 320
}

Malaysian Food Recognition 2

Dataset Versions

2024-11-08 3:27am

Popular Download Formats

1819 Total Images

Dataset Split

Preprocessing

Augmentations

Similar Projects

Annotations

Unused Classes

Tags

Attributes

42.jpg

Updated May 12, 56824

Generated by Roboflow

Training Set

Transforms

Annotation History

Raw Data