Conversion of Dataset from Darknet Format into Supervisely Format via Python.

Convert supervisely output to COCO keypoint data format

Takes the 'ann' metadata folder of a supervisely dataset and converts all bitmaps to rectangles

Use your yolov5 predictions as supervisely annotations

Visual diff and merge tool compare projects tags and classes

Find row in CSV file and attach row data to image (as tags or as metadata)

Export Supervisely to Cityscapes

Research app to generate synthetic data for detection / segmentation / instance segmentation tasks

App allows to extract video frames to images project without labels.

import json data to images

Converts labeled video project to images

YOLOv5 to Supervisely format

Resize images and annotations

Copy selected tags from images to objects of selected classes

Create reference items for catalog from labeled project

Import videos from your cloud storage by copying data or by link

Export Images metadata from project to json files

Reference objects are grouped into batches by columns from CSV catalog

App downloads videos and then uploads them to Supervisely Storage. Video file has to be in Supervisely's internal storage to provide fast processing speed during labeling.

App signs up users from CSV file. Available only for users with admin permissions or in Enterprise Edition