Conversion of Dataset from Darknet Format into Supervisely Format via Python.
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Updated
Aug 4, 2020 - Python
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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
Resize images and annotations
Copy selected tags from images to objects of selected classes
Create reference items for catalog from labeled project
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
Counts number of objects (instances), their figures, and number of frames that have object of specific class.
Copy images project from one Supervisely Instance to another (including annotations and images metadata).
General overview of all labeling jobs in team
Compare and merge two images projects: datasets / images / images metadata / image ta C987 gs / and annotations
Supervisely project to YOLOv5 format (downloadable tar archive)
Convert Supervisely to Pascal VOC
Export Supervisely to Cityscapes
Add a description, image, and links to the supervisely topic page so that developers can more easily learn about it.
To associate your repository with the supervisely topic, visit your repo's landing page and select "manage topics."