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Import

Upload your assets from PC or cloud storage, in many formats

83 results found

Images

Import Images

Drag and drop images to Supervisely, supported formats: .jpg, .jpeg, jpe, .mpo, .bmp, .png, .tiff, .tif, .webp, .nrrd

Import images in Supervisely format

Images with corresponding annotations

Convert YOLO v5 to Supervisely format

Transform YOLO v5 format to supervisely project

Import images from cloud storage

Import images from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)

Import Images from CSV

Upload images using .CSV file

Import images with masks

Import images with binary masks as annotations

Import COCO

Converts COCO format to Supervisely

Import dicom studies

Convert DICOM data to nrrd format and creates a new project with images grouped by selected metadata

Import Pascal VOC

Import public or custom data in Pascal VOC format to Supervisely

Remote import

Connect your remote storage and import data without duplication. Data is stored on your server but visible in Supervisely

Import from Google Cloud Storage

Upload images by reading links (Google Cloud Storage) from CSV file

Copy project between instances

Copies images + annotations + images metadata

CSV Products Catalog to Images Project

Convert .CSV catalog to Images Project

Import Cityscapes

Import Cityscapes to Supervisely

Import Metadata

Import Metadata for Images in Project

Import images groups

Import images groups connected via user defined tag

Pexels downloader

Downloads images from the Pexels to the dataset.

Import COCO Keypoints

Converts COCO Keypoints format to Supervisely

Add properties to image from CSV

Match image tag with CSV columns and add row values to image

Labelbox to Supervisely Migration Tool

Convert and copy multiple Labelbox projects into Supervisely at once.

Flickr downloader

Downloads images from the Flickr to the dataset.

Movie genre from its poster

Application imports kaggle dataset 'Movie genre from its poster' as supervisely project

Import image projects in Supervisely format from cloud storage

Import image projects in Supervisely format from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)

Import PDF as Images

Drag and drop PDFs to import pages as images to Supervisely

Roboflow to Supervisely Migration Tool

Convert and copy multiple Roboflow projects into Supervisely at once.

Import Multispectral Images

Import multispectral images as channels or as separate images.

Import CVAT

Import images and videos with annotations in CVAT format.

CVAT to Supervisely Migration Tool

Convert and copy multiple CVAT projects into Supervisely at once.

Import V7

Import images and videos with annotations in V7 format.

V7 to Supervisely Migration Tool

Convert and copy multiple V7 datasets into Supervisely at once.

Lemons (Annotated)

Lemons (Annotated)

6 images with annotated lemons and kiwifruits

Persons

Persons

Image project with person instances

Snacks catalog

Snacks catalog

Labeled images: snacks: chips / crisps / mix

Lemons (Test)

Lemons (Test)

Sample images project without labels

Country Roads

Country Roads

Labeled roads (sample: 100 images, full version: 1000 images)

Demo Images

Demo Images

17 unlabeled images for quick tests

Roads (Test)

Roads (Test)

156 unlabeled images with roads

Grocery store shelves

Labeled images of products on the shelve: snacks, chips, crisps

Roads (Annotated)

Roads (Annotated)

10 images with labeled road

Top 10 cat breeds

Top 10 cat breeds

Tag (name of breed) is assigned to every image

Country Roads (Test)

Country Roads (Test)

594 unlabeled images

PascalVOC GT Masks (Sample)

PascalVOC GT Masks (Sample)

726 sample gt-labeled images

Seeds

Seeds

Unlabeled images: sunflower / pumpkin (peeled + unpeeled) / mix

Tomatoes (Annotated)

Tomatoes (Annotated)

Project with 66 annotated tomatoes (424 images)

PascalVOC GT BBoxes (Sample)

PascalVOC GT BBoxes (Sample)

1171 sample gt-labeled images

Cats quiz

Cats quiz

What breed is this cat? demo for visual tagging app

PascalVOC PRED BBoxes (Sample)

PascalVOC PRED BBoxes (Sample)

1171 sample prediction-labeled images

PascalVOC PRED Masks (Sample)

PascalVOC PRED Masks (Sample)

726 sample pred-labeled images

Cracks Synthetic Dataset

Synthetic dataset for cracks segmentation

Images with alpha channel

Images with alpha channel

Illustrates alpha support in Supervisely

Train dataset - Insulator-Defect Detection

For object detection tutorials

Test dataset - Insulator-Defect Detection

For object detection tutorials

Train dataset - Eschikon Wheat Segmentation (EWS)

Images of wheat for training and validation

Test dataset - Eschikon Wheat Segmentation (EWS)

Wheat images for test

Videos

Import Videos

Import Videos without annotations to Supervisely

Import videos from cloud storage

Import videos from cloud (Google Cloud Storage, Amazon S3, Microsoft Azure, ...)

Import videos in Supervisely format

Import videos with annotations in Supervisely format

Import videos by URLs from txt file

Downloads videos by URLs and uploads them to Supervisely Storage

Import YouTube videos

Import videos by urls provided in text file

YouTube Downloader

Downloads and trim video from Youtube.

Labelbox to Supervisely Migration Tool

Convert and copy multiple Labelbox projects into Supervisely at once.

Import Videos from Team Files

Import selected videos from Team Files to selected destination

Import CVAT

Import images and videos with annotations in CVAT format.

CVAT to Supervisely Migration Tool

Convert and copy multiple CVAT projects into Supervisely at once.

Import V7

Import images and videos with annotations in V7 format.

V7 to Supervisely Migration Tool

Convert and copy multiple V7 datasets into Supervisely at once.

Videos example

Videos example

Sample videos with labels

Demo video pairs

Demo video pairs

Video pairs for multicamera labeling

Point clouds

Import Pointclouds PCD

Import pointclouds in PCD format without annotations

Import Pointcloud Episodes

Import Pointcloud Episodes with Annotations and Photo context

Import Pointclouds PLY

Import pointclouds without annotations in .ply format from Team Files

Import Point Cloud Project

Import Point Cloud Project with Annotations and Photo context in Supervisely format

Import KITTI 3D

Converts KITTI 3D format to Supervisely pointcloud format

Import LAS/LAZ format

Import LAS/LAZ format files to Supervisely 3D point cloud labeling tool

Import KITTI-360

Import Pointcloud Episodes from KITTI-360 format

Demo pointcloud project

30 pointclouds without annotations

Demo pointcloud project with labels

30 pointclouds with annotations

Demo LYFT 3D dataset

Demo LYFT 3D dataset

Demo project with pointcloud episodes from LYFT 3D dataset without labels

Demo LYFT 3D dataset annotated

Demo LYFT 3D dataset annotated

Demo project with pointcloud episodes from LYFT 3D dataset with labels

Demo KITTI pointcloud episodes annotated

Demo KITTI pointcloud episodes annotated

Demo project with pointcloud episodes from KITTI dataset with labels

Demo KITTI pointcloud episodes

Demo KITTI pointcloud episodes

Demo project with pointcloud episodes from KITTI dataset without labels

DICOM

Import dicom studies

Convert DICOM data to nrrd format and creates a new project with images grouped by selected metadata

Import DICOM Volumes

Import volumes in DICOM and NRRD formats without annotations

Import Volumes in Supervisely format

Import Supervisely volumes project with annotations

Demo volumes with labels

Demo volumes with labels

Project with labeled dicom and nrrd volumes

Demo volumes

Demo volumes

Demo project with dicom / nrrd volumes without labels