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On this page
  • Introduction
  • Function signature
  • Parameters
  • columns_number
  • default_opacity
  • fill_rectangle
  • border_width
  • view_height
  • empty_message
  • widget_id
  • Methods and attributes
  • Mini App Example
  • Import libraries
  • Init API client
  • Get project ID and dataset ID
  • Get images and annotations infos
  • Option 1. Collect image names, URLs, annotations and generate annotation names from server
  • Option 2. You can also serve images from your local machine, using a static directory
  • Create a function to modify the annotation
  • Iterate over column numbers and append modified annotations to widget
  • Create buttons for changing current image and cleaning up widget
  • Create app layout
  • Create app using layout
  • Create a callback functions for buttons

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  1. App development
  2. Widgets
  3. Compare Data

CompareAnnotations

PreviousClassBalanceNextObjects binding

Last updated 6 months ago

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Introduction

CompareAnnotations is a simple widget that allows you to compare different annotations for one image. It can be useful for comparing annotations of different applied NN models. Widget doesn't support Keypoints shape. This widget is based on widget.

Function signature

CompareAnnotations(
        columns_number=5,
        default_opacity=0.5,
        fill_rectangle=True,
        border_width=3,
        view_height=None,
        empty_message="No image was provided",
        widget_id=None,
)

Parameters

Parameters
Type
Description

columns_number

int

Determines number of columns in widget

default_opacity

float

Figures opacity

fill_rectangle

bool

If False labels with shape Rectangle will be hollow

border_width

int

Border width

view_height

int

Set fixed gallery height in px

empty_message

str

If no image is given, this message will be displayed.

widget_id

str

Id of the widget

columns_number

Determines the number of columns on CompareAnnotations.

type: int

default value: 1

compare_annotations = CompareAnnotations(columns_number=2)

default_opacity

Figures opacity.

type: float

default value: 0.5

compare_annotations = CompareAnnotations(columns_number=3, default_opacity=1)

fill_rectangle

If False labels with shape Rectangle will be hollow.

type: bool

default value: true

compare_annotations = CompareAnnotations(columns_number=3, fill_rectangle=False)

border_width

Determines border width to rectangle figures.

type: int

default value: 3

compare_annotations = CompareAnnotations(columns_number=3, border_width=10)

view_height

Set fixed gallery height in px.

type: int

default value: None

compare_annotations = CompareAnnotations(columns_number=3, view_height=300)

empty_message

If no image is given, this message will be displayed.

type: str

default value: "No image was provided"

compare_annotations = CompareAnnotations(columns_number=3, empty_message="Set image URL and annotations")

widget_id

ID of the widget.

type: str

default value: None

Methods and attributes

Attributes and Methods
Description

image_url()

Returns current image URL

set_image_url()

Set current image by URL

append()

Add annotations to gallery

is_empty()

Checks whether image is set or not

clean_up()

Clean up widget from image and annotations

Mini App Example

In this example, we will use CompareAnnotations widget to display different annotations for one image. We will modify and duplicate an existing image annotation and slightly alter the labels on it, to make them different. All labels will be converted to shape Rectangle.

You can find this example in our Github repository:

Import libraries

import os
from random import choice
import supervisely as sly
from dotenv import load_dotenv
from supervisely.app.widgets import (
    Button,
    Card,
    Container,
    CompareAnnotations,
)

from supervisely import Annotation, Rectangle

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()

Get project ID and dataset ID

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

Get images and annotations infos

project_meta = sly.ProjectMeta.from_json(data=api.project.get_meta(id=project_id))
images_infos = api.image.get_list(dataset_id=dataset_id)
anns_infos = api.annotation.get_list(dataset_id=dataset_id)

Option 1. Collect image names, URLs, annotations and generate annotation names from server

image_names = []
image_urls = []
image_anns = []
for idx in range(len(images_infos)):
    image_names.append(images_infos[idx].name)
    image_urls.append(images_infos[idx].full_storage_url)
    image_anns.append(
        sly.Annotation.from_json(data=anns_infos[idx].annotation, project_meta=project_meta)
    )

ann_names = [f"Model inference {idx+1}" for idx in range(len(image_anns))]

Option 2. You can also serve images from your local machine, using a static directory

Sort lists of images and annotations to make sure they are in the correct order.

static_dir = Path("compare data/005_compare_annotations/images")
ann_dir = Path("compare data/005_compare_annotations/annotations")

image_urls = sorted([
    f"/static/{get_file_name_with_ext(path)}"
    for path in static_dir.iterdir()
    if path.is_file()
])

local_annotations = sorted([str(path) for path in ann_dir.iterdir() if path.is_file()])

Read annotations from local .json files

image_anns = []
for local_ann in local_annotations:
    ann = sly.Annotation.from_json(
        data=sly.json.load_json_file(local_ann), project_meta=project_meta
    )
    image_anns.append(ann)

Create a function to modify the annotation

def ann_to_bbox(annotation: Annotation):
    labels = []
    mapping = {}
    for label in annotation.labels:
        if label.obj_class.name not in mapping:
            new_obj_class = sly.ObjClass(label.obj_class.name, Rectangle)
            mapping[label.obj_class] = new_obj_class
            label = label.scale(choice(range(90, 100)) / 100)
            labels.append(label)
    annotation = annotation.clone(labels=labels)
    annotation = annotation.to_detection_task(mapping)
    return annotation

Iterate over column numbers and append modified annotations to widget

We iterate over column numbers for demo purposes to show all annotations in one line.

for i in range(compare_annotations.columns_number):
    ann = ann_to_bbox(image_anns[0])
    compare_annotations.append(
        annotation=ann,
        title=ann_names[i],
        column_index=i,
    )

Create buttons for changing current image and cleaning up widget

change_image_btn = Button("Change image")
clean_up_btn = Button("Clean up")

Create app layout

Prepare a layout for app using Card widget with the content parameter and place widget that we've just created in the Container widget.

card = Card(
    "Compare Annotations",
    content=Container([compare_annotations, change_image_btn, clean_up_btn]),
)

layout = card

Create app using layout

Create an app object with layout parameter.

app = sly.Application(layout=layout)

In case you want to use a static directory, you need to pass it to the Application.

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

Create a callback functions for buttons

@clean_up_btn.click
def clean_up():
    compare_annotations.clean_up()


@change_image_btn.click
def set_image():
    compare_annotations.clean_up()
    rnd_idx = choice(range(len(images_infos)))
    compare_annotations.set_image_url(image_urls[rnd_idx])
    for i in range(compare_annotations.columns_number):
        ann = ann_to_bbox(image_anns[rnd_idx])
        compare_annotations.append(
            annotation=ann,
            title=f"{ann_names[i]}",
            column_index=i,
        )

This app requires that you project have at least 2 images in it. If you don't have any projects, you can get one from .

🔥
supervisely-ecosystem/ui-widgets-demos/compare-data/005_compare_annotations/src/main.py
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