
# Dataset: Mobile UI Design Detection

## Introduction

This dataset is designed for object detection tasks with a focus on detecting elements in mobile UI designs. The targeted objects include text, images, and groups. The dataset contains images and object detection boxes, including class labels and location information.

## Dataset Content

Load the dataset and take a look at an example:

```python
>>> from datasets import load_dataset
>>>> ds = load_dataset("mrtoy/mobile-ui-design")
>>> example = ds[0]
>>> example
{'width': 375,
 'height': 667,
 'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=375x667>,
 'objects': {'bbox': [[0.0, 0.0, 375.0, 667.0],
   [0.0, 0.0, 375.0, 667.0],
   [0.0, 0.0, 375.0, 20.0],
   ...
  ],
  'category': ['text',
   'rectangle',
   'rectangle',
   ...]}}
```

The dataset has the following fields:

- image: PIL.Image.Image object containing the image.
- height: The image height.
- width: The image width.
- objects: A dictionary containing bounding box metadata for the objects in the image:
    - bbox: The object’s bounding box (xmin,ymin,width,height).
    - category: The object’s category, with possible values including rectangle、text、group、image
    - color: The object’s color, text color or rectangle color, or None
    - radius: The object’s color, rectangle radius, or None
    - text: text content, or None

You can visualize the bboxes on the image using some internal torch utilities. 

```python
import torch
from torchvision.ops import box_convert
from torchvision.utils import draw_bounding_boxes
from torchvision.transforms.functional import pil_to_tensor, to_pil_image

item = ds[0]
boxes_xywh = torch.tensor(item['objects']['bbox'])
boxes_xyxy = box_convert(boxes_xywh, 'xywh', 'xyxy')
to_pil_image(
    draw_bounding_boxes(
        pil_to_tensor(item['image']),
        boxes_xyxy,
        labels=item['objects']['category'],
    )
)
```
![image](9b8671a5-b529-41dc-b951-b29a8b29da64.png)

![image](11c03c2c-39ac-442b-9c1a-67e1e0a2aea7.png)

![image](ec197c72-f8ba-4f79-81fa-ceaf533cb5e3.png)

## Applications

This dataset can be used for various applications, such as:

- Training and evaluating object detection models for mobile UI designs.
- Identifying design patterns and trends to aid UI designers and developers in creating high-quality mobile app UIs.
- Enhancing the automation process in generating UI design templates.
- Improving image recognition and analysis in the field of mobile UI design.


task_categories:object-detection size_categories:n<1K license:apache-2.0 ui design detection region:us
{"license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["object-detection"], "dataset_info": {"features": [{"name": "width", "dtype": "int64"}, {"name": "height", "dtype": "int64"}, {"name": "image", "dtype": "image"}, {"name": "objects", "struct": [{"name": "bbox", "sequence": {"sequence": "float64"}}, {"name": "category", "sequence": "string"}, {"name": "color", "list": [{"name": "alpha", "dtype": "float64"}, {"name": "blue", "dtype": "float64"}, {"name": "green", "dtype": "float64"}, {"name": "red", "dtype": "float64"}]}, {"name": "radius", "sequence": "float64"}, {"name": "text", "sequence": "string"}]}], "splits": [{"name": "train", "num_bytes": 1253458059.322, "num_examples": 7846}], "download_size": 1160884066, "dataset_size": 1253458059.322}, "tags": ["ui", "design", "detection"]}
TAGS
#task_categories-object-detection #size_categories-n<1K #license-apache-2.0 #ui #design #detection #region-us 


# Dataset: Mobile UI Design Detection

## Introduction

This dataset is designed for object detection tasks with a focus on detecting elements in mobile UI designs. The targeted objects include text, images, and groups. The dataset contains images and object detection boxes, including class labels and location information.

## Dataset Content

Load the dataset and take a look at an example:



The dataset has the following fields:

- image: PIL.Image.Image object containing the image.
- height: The image height.
- width: The image width.
- objects: A dictionary containing bounding box metadata for the objects in the image:
    - bbox: The object’s bounding box (xmin,ymin,width,height).
    - category: The object’s category, with possible values including rectangle、text、group、image
    - color: The object’s color, text color or rectangle color, or None
    - radius: The object’s color, rectangle radius, or None
    - text: text content, or None

You can visualize the bboxes on the image using some internal torch utilities. 


!image

!image

!image

## Applications

This dataset can be used for various applications, such as:

- Training and evaluating object detection models for mobile UI designs.
- Identifying design patterns and trends to aid UI designers and developers in creating high-quality mobile app UIs.
- Enhancing the automation process in generating UI design templates.
- Improving image recognition and analysis in the field of mobile UI design.


# Dataset: Mobile UI Design Detection ## Introduction

This dataset is designed for object detection tasks with a focus on detecting elements in mobile UI designs. The targeted objects include text, images, and groups. The dataset contains images and object detection boxes, including class labels and location information. ## Dataset Content

Load the dataset and take a look at an example:



The dataset has the following fields:

- image: PIL.Image.Image object containing the image.
- height: The image height.
- width: The image width.
- objects: A dictionary containing bounding box metadata for the objects in the image:
    - bbox: The object’s bounding box (xmin,ymin,width,height).
    - category: The object’s category, with possible values including rectangle、text、group、image
    - color: The object’s color, text color or rectangle color, or None
    - radius: The object’s color, rectangle radius, or None
    - text: text content, or None

You can visualize the bboxes on the image using some internal torch utilities. 


!image

!image

!image ## Applications

This dataset can be used for various applications, such as:

- Training and evaluating object detection models for mobile UI designs.
- Identifying design patterns and trends to aid UI designers and developers in creating high-quality mobile app UIs.
- Enhancing the automation process in generating UI design templates.
- Improving image recognition and analysis in the field of mobile UI design.
TAGS
#task_categories-object-detection #size_categories-n<1K #license-apache-2.0 #ui #design #detection #region-us 
 # Dataset: Mobile UI Design Detection ## Introduction

This dataset is designed for object detection tasks with a focus on detecting elements in mobile UI designs. The targeted objects include text, images, and groups. The dataset contains images and object detection boxes, including class labels and location information. ## Dataset Content

Load the dataset and take a look at an example:



The dataset has the following fields:

- image: PIL.Image.Image object containing the image.
- height: The image height.
- width: The image width.
- objects: A dictionary containing bounding box metadata for the objects in the image:
    - bbox: The object’s bounding box (xmin,ymin,width,height).
    - category: The object’s category, with possible values including rectangle、text、group、image
    - color: The object’s color, text color or rectangle color, or None
    - radius: The object’s color, rectangle radius, or None
    - text: text content, or None

You can visualize the bboxes on the image using some internal torch utilities. 


!image

!image

!image ## Applications

This dataset can be used for various applications, such as:

- Training and evaluating object detection models for mobile UI designs.
- Identifying design patterns and trends to aid UI designers and developers in creating high-quality mobile app UIs.
- Enhancing the automation process in generating UI design templates.
- Improving image recognition and analysis in the field of mobile UI design.
passage: TAGS
#task_categories-object-detection #size_categories-n<1K #license-apache-2.0 #ui #design #detection #region-us 
# Dataset: Mobile UI Design Detection## Introduction

This dataset is designed for object detection tasks with a focus on detecting elements in mobile UI designs. The targeted objects include text, images, and groups. The dataset contains images and object detection boxes, including class labels and location information.## Dataset Content

Load the dataset and take a look at an example:



The dataset has the following fields:

- image: PIL.Image.Image object containing the image.
- height: The image height.
- width: The image width.
- objects: A dictionary containing bounding box metadata for the objects in the image:
    - bbox: The object’s bounding box (xmin,ymin,width,height).
    - category: The object’s category, with possible values including rectangle、text、group、image
    - color: The object’s color, text color or rectangle color, or None
    - radius: The object’s color, rectangle radius, or None
    - text: text content, or None

You can visualize the bboxes on the image using some internal torch utilities. 


!image

!image

!image## Applications

This dataset can be used for various applications, such as:

- Training and evaluating object detection models for mobile UI designs.
- Identifying design patterns and trends to aid UI designers and developers in creating high-quality mobile app UIs.
- Enhancing the automation process in generating UI design templates.
- Improving image recognition and analysis in the field of mobile UI design.