Import Images
Drag and drop images to Supervisely, supported formats: .jpg, .jpeg, jpe, .mpo, .bmp, .png, .tiff, .tif, .webp, .nrrd
Upload your assets from PC or cloud storage, in many formats
Drag and drop images to Supervisely, supported formats: .jpg, .jpeg, jpe, .mpo, .bmp, .png, .tiff, .tif, .webp, .nrrd
Images with corresponding annotations
Transform YOLO v5 format to supervisely project
Import images from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)
Upload images using .CSV file
Import images with binary masks as annotations
Converts COCO format to Supervisely
Convert DICOM data to nrrd format and creates a new project with images grouped by selected metadata
Import public or custom data in Pascal VOC format to Supervisely
Connect your remote storage and import data without duplication. Data is stored on your server but visible in Supervisely
Upload images by reading links (Google Cloud Storage) from CSV file
Copies images + annotations + images metadata
Convert .CSV catalog to Images Project
Import Cityscapes to Supervisely
Import Metadata for Images in Project
Import images groups connected via user defined tag
Downloads images from the Pexels to the dataset.
Converts COCO Keypoints format to Supervisely
Match image tag with CSV columns and add row values to image
Convert and copy multiple Labelbox projects into Supervisely at once.
Downloads images from the Flickr to the dataset.
Application imports kaggle dataset 'Movie genre from its poster' as supervisely project
Import image projects in Supervisely format from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)
Drag and drop PDFs to import pages as images to Supervisely
Convert and copy multiple Roboflow projects into Supervisely at once.
Import multispectral images as channels or as separate images.
Import images and videos with annotations in CVAT format.
Convert and copy multiple CVAT projects into Supervisely at once.
Import images and videos with annotations in V7 format.
Convert and copy multiple V7 datasets into Supervisely at once.
6 images with annotated lemons and kiwifruits
Image project with person instances
Labeled images: snacks: chips / crisps / mix
Sample images project without labels
Labeled roads (sample: 100 images, full version: 1000 images)
17 unlabeled images for quick tests
156 unlabeled images with roads
Labeled images of products on the shelve: snacks, chips, crisps
10 images with labeled road
Tag (name of breed) is assigned to every image
594 unlabeled images
726 sample gt-labeled images
Unlabeled images: sunflower / pumpkin (peeled + unpeeled) / mix
Project with 66 annotated tomatoes (424 images)
1171 sample gt-labeled images
What breed is this cat? demo for visual tagging app
1171 sample prediction-labeled images
726 sample pred-labeled images
Synthetic dataset for cracks segmentation
Illustrates alpha support in Supervisely
For object detection tutorials
For object detection tutorials
Images of wheat for training and validation
Wheat images for test
Import Videos without annotations to Supervisely
Import videos from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)
Import videos with annotations in Supervisely format
Downloads videos by URLs and uploads them to Supervisely Storage
Import videos by urls provided in text file
Downloads and trim video from Youtube.
Convert and copy multiple Labelbox projects into Supervisely at once.
Import selected videos from Team Files to selected destination
Import images and videos with annotations in CVAT format.
Convert and copy multiple CVAT projects into Supervisely at once.
Import images and videos with annotations in V7 format.
Convert and copy multiple V7 datasets into Supervisely at once.
Sample videos with labels
Video pairs for multicamera labeling
Import pointclouds in PCD format without annotations
Import Pointcloud Episodes with Annotations and Photo context
Import pointclouds without annotations in .ply format from Team Files
Import Point Cloud Project with Annotations and Photo context in Supervisely format
Converts KITTI 3D format to Supervisely pointcloud format
Import LAS/LAZ format files to Supervisely 3D point cloud labeling tool
Import Pointcloud Episodes from KITTI-360 format
30 pointclouds without annotations
30 pointclouds with annotations
Demo project with pointcloud episodes from LYFT 3D dataset without labels
Demo project with pointcloud episodes from LYFT 3D dataset with labels
Demo project with pointcloud episodes from KITTI dataset with labels
Demo project with pointcloud episodes from KITTI dataset without labels
Convert DICOM data to nrrd format and creates a new project with images grouped by selected metadata
Import volumes in DICOM and NRRD formats without annotations
Import Supervisely volumes project with annotations
Project with labeled dicom and nrrd volumes
Demo project with dicom / nrrd volumes without labels