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Versions
2023-07-22 2:07pm
v9
·
2 years ago
2023-07-22 10:47am
v8
·
2 years ago
2023-06-24 9:25pm
v7
·
2 years ago
2023-06-24 9:06pm
v6
·
2 years ago
2023-04-20 11:38pm
v5
·
2 years ago
2023-04-20 11:02pm
v4
·
2 years ago
2023-04-20 10:54pm
v3
·
2 years ago
2023-03-20 3:50pm
v2
·
2 years ago
2023-02-26 8:37pm
v1
·
2 years ago
v7

2023-06-24 9:25pm

Generated on Jun 24, 2023
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478 Total Images

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Dataset Split

Train Set 50%
237Images
Valid Set 5%
24Images
Test Set 45%
217Images

Preprocessing

Auto-Orient: Applied
Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Saturation: Between -11% and +11%
Brightness: Between -9% and +9%
Exposure: Between -14% and +14%
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise, Upside Down

Similar Projects

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Capstone chips detection
Annotate
1 / 13
Show/hide annotations(H)
train
Labels
Attributes
Raw Data

Annotations

Group:
Chips

Classes

Layers

 
Average chips
2
 
Bad chips
6
 
Good chips
2

Unused Classes

1
2
3
bad Chocolate
good Chocolate

Tags

No Tags Applied
Type and select tags below to add them to the image.

Attributes

IMG20230225160056_augmented.jpg

640x640
0.41MP

Updated Aug 13, 55448

3:49PM
GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient Applied
Resize Stretch to 640x640
Flip Applied Per Bounding Box
90° Rotate Applied Per Bounding Box
Flip Both
90° Rotate Applied
Saturation 11%
Brightness 0%
Exposure 7%

Annotation History

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Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "xNUIurM7L95zgDaDYVsm"
    ],
    "destination": "8a6bf300410690e3dc451d8c23805289",
    "height": 640,
    "id": "9M3bZbGKkulreZ1Yo4IX",
    "label": [],
    "labels": [],
    "name": "IMG20230225160056_augmented.jpg",
    "numSteps": 9,
    "owner": "er5VM4GD1nYlKa2Fzwwr0UBxYty1",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",640,640]",
        "flip:[[\"both\"],[],[],[\"both\"],[\"horizontal\"],[],[],[\"both\"],[\"vertical\"],[]]",
        "ninety:[[-90],[180],[90],[180],[0],[180],[0],[180],[180],[90]]",
        "flip:[\"both\"]",
        "ninety:[0]",
        "saturation:[11]",
        "brightness:[0]",
        "exposure:[7]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 640x640"
        },
        {
            "name": "Flip",
            "value": "Applied Per Bounding Box"
        },
        {
            "name": "90° Rotate",
            "value": "Applied Per Bounding Box"
        },
        {
            "name": "Flip",
            "value": "Both"
        },
        {
            "name": "90° Rotate",
            "value": "Applied"
        },
        {
            "name": "Saturation",
            "value": "11%"
        },
        {
            "name": "Brightness",
            "value": "0%"
        },
        {
            "name": "Exposure",
            "value": "7%"
        }
    ],
    "source": "9M3bZbGKkulreZ1Yo4IX",
    "split": "train",
    "split.xNUIurM7L95zgDaDYVsm.7": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,640]\",\n    \"flip:[[\\\"both\\\"],[],[],[\\\"both\\\"],[\\\"horizontal\\\"],[],[],[\\\"both\\\"],[\\\"vertical\\\"],[]]\",\n    \"ninety:[[-90],[180],[90],[180],[0],[180],[0],[180],[180],[90]]\",\n    \"flip:[\\\"both\\\"]\",\n    \"ninety:[0]\",\n    \"saturation:[11]\",\n    \"brightness:[0]\",\n    \"exposure:[7]\"\n]",
    "updated": 1687622140160,
    "updatedDate": "Aug 13, 55448",
    "updatedTime": "3:49PM",
    "updatedTimezone": "+00:00",
    "versions": [
        "xNUIurM7L95zgDaDYVsm/7"
    ],
    "width": 640
}

Annotation Data

{
    "boxes": [
        {
            "label": "Bad chips",
            "x": 321,
            "y": 499,
            "width": 178,
            "height": 178
        },
        {
            "label": "Bad chips",
            "x": 520,
            "y": 452,
            "width": 162,
            "height": 132
        },
        {
            "label": "Bad chips",
            "x": 175.5,
            "y": 377.5,
            "width": 112,
            "height": 112
        },
        {
            "label": "Bad chips",
            "x": 334,
            "y": 225,
            "width": 216,
            "height": 138
        },
        {
            "label": "Bad chips",
            "x": 134.5,
            "y": 235,
            "width": 191,
            "height": 136
        },
        {
            "label": "Bad chips",
            "x": 228.5,
            "y": 104.5,
            "width": 131,
            "height": 117
        },
        {
            "label": "Average chips",
            "x": 506,
            "y": 300.5,
            "width": 178,
            "height": 136
        },
        {
            "label": "Good chips",
            "x": 337,
            "y": 366.5,
            "width": 148,
            "height": 107
        },
        {
            "label": "Average chips",
            "x": 397.5,
            "y": 94.5,
            "width": 145,
            "height": 130
        },
        {
            "label": "Good chips",
            "x": 560.5,
            "y": 157.5,
            "width": 109,
            "height": 109
        }
    ],
    "height": 640,
    "key": "IMG20230225160056_augmented.jpg",
    "width": 640
}

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