Use your yolov5 predictions as supervisely annotations

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

Compare and merge two images projects: datasets / images / images metadata / image tags / and annotations

Copy selected tags from images to objects of selected classes

Visual diff and merge tool compare projects tags and classes

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

YOLOv5 to Supervisely format

Convert supervisely output to COCO keypoint data format

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

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

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

Counts number of objects (instances), their figures, and number of frames that have object of specific class.

Resize images and annotations

Convert Supervisely to Pascal VOC

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

Reference objects are grouped into batches by columns from CSV catalog

Supervisely project to YOLOv5 format (downloadable tar archive)

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

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.

General overview of all labeling jobs in team