ClassBalance

Introduction

ClassBalance is a widget in Supervisely that allows for displaying input data classes balance on the UI. For example, you can display the distribution of tags to different classes in the project, or set your data according to the required format. It also provides functionality for data streaming and dynamic updates, allowing the class balance to display real-time data. Additionally, users can control the widget through Python code by detecting events such as clicking on a class name or segment data.

Function signature

ClassBalance(
    segments=[],
    rows_data=[],
    slider_data={},
    max_value=None,
    max_height=350,
    rows_height=100,
    selectable=True,
    collapsable=False,
    clickable_name=False,
    clickable_segment=False,
    widget_id=None,
)

Example of input data we will use. If max_value is None, the maximum total form rows_data will be taken as max_value.

max_value = 1000
segments = [
    {"name": "train", "key": "train", "color": "#1892f8"},
    {"name": "val", "key": "val", "color": "#25e298"},
    {"name": "test", "key": "test", "color": "#fcaf33"},
]

rows_data = [
    {
        "nameHtml": "<strong>black-pawn</strong>",
        "name": "black-pawn",
        "total": 1000,
        "disabled": False,
        "segments": {"train": 600, "val": 350, "test": 50},
    },
    {
        "nameHtml": "<strong>white-pawn</strong>",
        "name": "white-pawn",
        "total": 700,
        "disabled": False,
        "segments": {"train": 400, "val": 250, "test": 50},
    },
]

slider_data = {
    "black-pawn": [
        {
            "moreExamples": ["https://www.w3schools.com/howto/img_nature.jpg"],
            "preview": "https://www.w3schools.com/howto/img_nature.jpg",
        }
    ],
    "white-pawn": [
        {
            "moreExamples": ["https://i.imgur.com/35pUPD2.jpg"],
            "preview": "https://i.imgur.com/35pUPD2.jpg",
        }
    ],
}

Parameters

Type

Description

segments

List[Dict]

List of segments in the widget

rows_data

List[Dict]

List of rows data in the widget

slider_data

Dict

Dict containing ClassBalance slider images

max_value

int

The maximum value of the row input data "total" field

max_height

int

Specifies the maximum height of the ClassBalance

rows_height

int

Specifies the height of the ClassBalance rows

selectable

bool

Determines if rows can be selected

collapsable

bool

Determines whether a rows data can be collapsed

clickable_name

bool

Allows clicking on class names

clickable_segment

bool

Allows clicking on class segments

widget_id

str

ID of the widget

segments

List of segments in the widget.

type: List[Dict]

default value: []

rows_data

List of rows data in the widget.

type: List[Dict]

default value: []

class_balance = ClassBalance(segments=segments, rows_data=rows_data)

slider_data

Dict containing images for row images sliders. It needs collapsable=True to be set.

type: Dict

default value: {}

class_balance = ClassBalance(
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    collapsable=True,
)

max_value

The maximum value of the row input data "total" field. If max_value is None, the maximum total form rows_data will be taken as max_value.

type: int

default value: None

class_balance = ClassBalance(
    max_value=2000,
    segments=segments,
    rows_data=rows_data,
)

max_height

Specifies the maximum height of the ClassBalance.

type: int

default value: 350

class_balance = ClassBalance(
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    collapsable=True
    max_height=250,
)

rows_height

Specifies the height of the ClassBalance rows.

type: int

default value: 100

class_balance = ClassBalance(
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    collapsable=True
    rows_height=200,
)

selectable

Determines whether a collapse button is displayed.

type: bool

default value: True

class_balance = ClassBalance(
    max_value=max_value,
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    selectable=False,
    collapsable=True
)

collapsable

Display the collapse button. The case collapsable=True has been shown above to show examples for changing the max_height parameter. So now an example will be shown for case collapsable=False.

type: bool

default value: False

class_balance = ClassBalance(
    max_value=max_value,
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    collapsable=False
)

clickable_name

Allows clicking on class names.

type: bool

default value: False

class_balance = ClassBalance(
    max_value=max_value,
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    clickable_name=True,
)

clickable_segment

Allow clicking on class segments.

type: bool

default value: False

class_balance = ClassBalance(
    max_value=max_value,
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    clickable_segment=True,
)

Methods and attributes

Attributes and Methods

Description

is_selectable

Returns True if ClassBalance rows is selectable, otherwise False

is_collapsable

Returns True if ClassBalance rows is collapsable, otherwise False

is_clickable_name

Returns True if ClassBalance rows name is clickable, otherwise False

is_clickable_segment

Returns True if ClassBalance rows segment is clickable, otherwise False

get_max_value()

Returns the maximum value of ClassBalance rows

set_max_value(value: int)

Sets the maximum value of ClassBalance rows

get_max_height()

Return ClassBalance max height.

set_max_height(value: int)

Sets the maximum height of ClassBalance

get_segments()

Return ClassBalance segments

add_segments(segments: List[Dict])

Add new segments to existing in ClassBalance

set_segments(segments: List[Dict])

Set new segments in ClassBalance

get_rows_data()

Return ClassBalance rows_data

add_rows_data(rows_data: List[Dict])

Add new rows_data to now existing in ClassBalance

set_rows_data(rows_data: List[Dict])

Set new rows_data in ClassBalance

get_slider_data()

Return ClassBalance slider_data

add_slider_data(slider_data: Dict)

Add new slider_data to now existing in ClassBalance

set_slider_data(slider_data: Dict)

Set new slider_data in ClassBalance

get_selected_rows()

Return list of ClassBalance selected rows

@click

Decorator function to handle clicks on class names or rows segments

Mini App Example

You can find this example in our Github repository:

supervisely-ecosystem/ui-widgets-demos/compare-data/004_class_balance/src/main.py

Import libraries

import os
from collections import defaultdict

from dotenv import load_dotenv
import supervisely as sly
from supervisely.app.widgets import Button, Card, ClassBalance, Container, Flexbox, Text
from supervisely.imaging.color import rgb2hex
from tqdm import tqdm

Init API client

First, we load environment variables with credentials and init API for communicating with Supervisely Instance:

if sly.is_development():
    load_dotenv("local.env")
    load_dotenv(os.path.expanduser("~/supervisely.env"))

api = sly.Api()

Prepare series for class balance

max_value = 1000
segments = [
    {"name": "train", "key": "train", "color": "#1892f8"},
    {"name": "val", "key": "val", "color": "#25e298"},
    {"name": "test", "key": "test", "color": "#fcaf33"},
]

rows_data = [
    {
        "nameHtml": "<strong>black-pawn</strong>",
        "name": "black-pawn",
        "total": 1000,
        "disabled": False,
        "segments": {"train": 600, "val": 350, "test": 50},
    },
    {
        "nameHtml": "<strong>white-pawn</strong>",
        "name": "white-pawn",
        "total": 700,
        "disabled": False,
        "segments": {"train": 400, "val": 250, "test": 50},
    },
]

slider_data = {
    "black-pawn": [
        {
            "moreExamples": ["https://www.w3schools.com/howto/img_nature.jpg"],
            "preview": "https://www.w3schools.com/howto/img_nature.jpg",
        }
    ],
    "white-pawn": [
        {
            "moreExamples": ["https://i.imgur.com/35pUPD2.jpg"],
            "preview": "https://i.imgur.com/35pUPD2.jpg",
        }
    ],
}

Initialize ClassBalance

class_balance_1 = ClassBalance(
    max_value=max_value,
    segments=segments,
    rows_data=rows_data,
    slider_data=slider_data,
    max_height=700,
    collapsable=True,
)

Create card widget with first ClassBalance widget content

card_1 = Card(
    title="Simple example how to use ClassBalance widget",
    content=Container([class_balance_1]),
    collapsable=True,
)
card_1.collapse()

👍 In this example, we will iterate through sample dataset images from the Supervisely platform and crop them based on object classes to set in the image slider. Finally, we will calculate and collect statistics for each class and display the class balance information.

Create static dir

Create a static directory to store the cropped images in local directory. Or you can upload them to the Team Files and use the full_storage_url to display them in the image slider.

static_dir = os.path.join(sly.app.get_data_dir(), "static")
sly.fs.mkdir(static_dir, remove_content_if_exists=True)

Get environment variables

project_id = sly.env.project_id()
dataset_id = sly.env.dataset_id()

Get ProjectMeta and DatasetInfo from the server

project_meta = sly.ProjectMeta.from_json(api.project.get_meta(project_id))
dataset = api.dataset.get_info_by_id(dataset_id)

Get all image infos, annotations and download images from server

image_infos = api.image.get_list(dataset.id)
image_ids = [image_info.id for image_info in image_infos]
imame_nps = api.image.download_nps(dataset.id, image_ids)
anns_json = api.annotation.download_json_batch(dataset.id, image_ids)
anns = [sly.Annotation.from_json(json, project_meta) for json in anns_json]

Calculate and collect series for the ClassBalance widget

PADDINGS = {"top": "20px", "left": "20px", "bottom": "20px", "right": "20px"}

progress = tqdm(desc=f"Processing datasets...", total=dataset.items_count)

# prepare data for ClassBalance widget
crop_id = 0
slider_data = defaultdict(list)
new_slider_data = defaultdict(list)
objclass_stats = defaultdict(lambda: defaultdict(lambda: 0))
# collect cropped images for image sliders
for image_info, img, ann in zip(image_infos, imame_nps, anns):
    for idx, objclass in enumerate(project_meta.obj_classes):
        # crop current image to separated images which contain current class instance
        crops = sly.aug.instance_crop(img, ann, objclass.name, False, PADDINGS)
        objclass_stats[objclass.name]["total"] += len(crops)

        for crop_img, crop_ann in crops:
            # draw annotations on image and upload result crop image to Team Files
            crop_ann.draw_pretty(crop_img)
            path = os.path.join(static_dir, f"{crop_id}-{image_info.name}")
            static_path = os.path.join("static", os.path.basename(path))
            crop_id += 1
            sly.image.write(path, crop_img)

            # collect cropped image paths for ClassBalance widget
            if idx == 0:
                slider_data[objclass.name].append({"preview": static_path})
            else:
                new_slider_data[objclass.name].append({"preview": static_path})

    # count number of objects with each tag
    for label in ann.labels:
        for tag in label.tags:
            objclass_stats[label.obj_class.name][tag.name] += 1

    progress.update(1)

# prepare rows data
rows_data = []
new_rows_data = []

tag_metas = project_meta.tag_metas
for idx, obj_class in enumerate(project_meta.obj_classes):
    data = {}
    data["name"] = obj_class.name
    data["nameHtml"] = f"<strong>{obj_class.name}</strong>"
    data["total"] = objclass_stats[obj_class.name]["total"]
    data["disabled"] = False
    data["segments"] = {}
    for tag_meta in tag_metas:
        data["segments"][tag_meta.name] = objclass_stats[obj_class.name][tag_meta.name]
    if idx == 0:
        rows_data.append(data)
    else:
        new_rows_data.append(data)

segments = [{"name": tm.name, "key": tm.name, "color": rgb2hex(tm.color)} for tm in tag_metas]

Initialize ClassBalance

class_balance_2 = ClassBalance(
    max_value=max([stat["total"] for stat in objclass_stats.values()]),
    segments=segments[:-1],
    rows_data=rows_data,
    slider_data=slider_data,
    max_height=700,
    collapsable=True,
    clickable_name=True,
    clickable_segment=True,
)

Create additional widgets

add_segment_btn = Button("Add segment")
add_row_btn = Button("Add row data")
add_slider_data_btn = Button("Add slider data")

buttons = Flexbox([add_segment_btn, add_row_btn, add_slider_data_btn], "horizontal")
text = Text()

card_2 = Card(
    title="Advanced example how to use ClassBalance widget",
    content=Container([class_balance_2, buttons, text]),
    collapsable=True,
)
card_2.collapse()

Create app layout

Prepare a layout for the app using Card widget with the content parameter.

layout = Container(widgets=[card_1, card_2])

Create app using layout

Create an app object with the layout and static_dir parameters.

app = sly.Application(layout=layout, static_dir=static_dir)

Add functions to control widgets from python code

@class_balance_2.click
def show_item(res):
    if res.get("segmentValue") is not None and res.get("segmentName") is not None:
        info = (
            f"Class {res['name']} contain {res['segmentValue']} tags with name {res['segmentName']}"
        )
        if res["segmentName"] == "val":
            status = "success"
        elif res["segmentName"] == "test":
            status = "warning"
        elif res["segmentName"] == "trash":
            status = "error"
        else:
            status = "info"
    else:
        info = f"Class {res['name']}"
        status = "text"

    text.set(text=info, status=status)


@add_segment_btn.click
def add_segment():
    class_balance_2.add_segments(segments[-1:])


@add_row_btn.click
def add_row():
    class_balance_2.add_rows_data(new_rows_data)


@add_slider_data_btn.click
def add_slider_data():
    class_balance_2.add_slider_data(new_slider_data)