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Custom weights

load custom weights from Team Files

Pretrained models

weights pretrained on popular datasets

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Detectron2 provides us Mask R-CNN Instance Segmentation
baselines based on 3 different backbone combinations

FPN: Use a ResNet+FPN backbone with standard conv and FC heads for mask and box prediction, respectively. It obtains the best speed/accuracy tradeoff, but the other two are still useful for research.
C4: Use a ResNet conv4 backbone with conv5 head. The original baseline in the Faster R-CNN paper.
DC5 (Dilated-C5): Use a ResNet conv5 backbone with dilations in conv5, and standard conv and FC heads for mask and box prediction, respectively. This is used by the Deformable ConvNet paper.

more about models
(find model using model id)

Types

Categories

popular

Import images app

Import images in Supervisely format app

Classes stats for images app

Import images from cloud storage app

Import Videos from Team Files app

Train YOLOv5 GPU app

Convert Supervisely to YOLO v5 format app

Import Images from CSV app

Import videos in Supervisely format app

Serve YOLOv5 GPU app

Import videos from cloud storage app

Import videos by URLs from txt file app

Import Pointclouds PLY app

RITM interactive segmentation SmartTool GPU app

Persons project

Create Trainset for SmartTool app

Import DICOM volumes app

Convert YOLO v5 to Supervisely format app

Convert Class Shape app

Import Pointcloud Episodes in Supervisely format app

Import Volumes in Supervisely format app

Export to Pascal VOC app

TransT object tracking (CVPR2021) GPU app

Videos project to images project app

Export to COCO app

Apply NN to Images Project app

NN Image Labeling app

Assign train/val tags to images app

Labeling Jobs Stats app

Flying objects app

Import dicom studies app

Merge classes app

Remote import app

Object Size Stats app

Country Roads project

Export YOLOv5 weights app

Train MMClassification GPU app

Import from Google Cloud Storage app

Labeling Events Stats app

ImgAug Studio app

Resize images app

Classes co-occurrence matrix app

Render Video Labels to MP4 app

Video objects stats for every class app

Add properties to image from CSV app

Sliding window split app

Country Roads (Test) project

Extract frames from videos app

Lemons (Annotated) project

Labeler First Time Through app

Diff and Merge Project Meta app

Rasterize objects on images app

Diff and Merge Images Projects app

Roads (Annotated) project

ilastik pixel classification app

Merge datasets app

Export as masks app

Export to Cityscapes app

Copy image tags to objects app

Grocery store shelves project

Lemons (Test) project

Train UNet GPU app

Batched Smart Tool app

AI assisted classification app

Unpack AnyShape Classes app

Synthetic videos for tracking app

Export activity as csv app

Export volumes in Supervisely format app

Export Pointcloud Episodes in Supervisely format app

Synthetic retail products app

Object detection metrics app

Create users from CSV app

Export to KITTI 3D app

Copy project between instances app

Create JSON with reference items app

Images project to videos project app

Sliding window merge app

Import images
app

Import images in Supervisely format
app

Classes stats for images
app

Import images from cloud storage
app

Import Videos from Team Files
app

Train YOLOv5 GPU
app

Convert Supervisely to YOLO v5 format
app

Import Images from CSV
app

Import videos in Supervisely format
app

Serve YOLOv5 GPU
app

Import videos from cloud storage
app

Import videos by URLs from txt file
app

Import Pointclouds PLY
app

RITM interactive segmentation SmartTool GPU
app

Persons
project

Create Trainset for SmartTool
app

Import DICOM volumes
app

Convert YOLO v5 to Supervisely format
app

Convert Class Shape
app

Import Pointcloud Episodes in Supervisely format
app

Import Volumes in Supervisely format
app

Export to Pascal VOC
app

TransT object tracking (CVPR2021) GPU
app

Videos project to images project
app

Export to COCO
app

Apply NN to Images Project
app

NN Image Labeling
app

Assign train/val tags to images
app

Labeling Jobs Stats
app

Flying objects
app

Import dicom studies
app

Merge classes
app

Remote import
app

Object Size Stats
app

Country Roads
project

Export YOLOv5 weights
app

Train MMClassification GPU
app

Import from Google Cloud Storage
app

Labeling Events Stats
app

ImgAug Studio
app

Resize images
app

Classes co-occurrence matrix
app

Render Video Labels to MP4
app

Video objects stats for every class
app

Add properties to image from CSV
app

Sliding window split
app

Country Roads (Test)
project

Extract frames from videos
app

Lemons (Annotated)
project

Labeler First Time Through
app

Diff and Merge Project Meta
app

Rasterize objects on images
app

Diff and Merge Images Projects
app

Roads (Annotated)
project

ilastik pixel classification
app

Merge datasets
app

Export as masks
app

Export to Cityscapes
app

Copy image tags to objects
app

Grocery store shelves
project

Lemons (Test)
project

Train UNet GPU
app

Batched Smart Tool
app

AI assisted classification
app

Unpack AnyShape Classes
app

Synthetic videos for tracking
app

Export activity as csv
app

Export volumes in Supervisely format
app

Export Pointcloud Episodes in Supervisely format
app

Synthetic retail products
app

Object detection metrics
app

Create users from CSV
app

Export to KITTI 3D
app

Copy project between instances
app

Create JSON with reference items
app

Images project to videos project
app

Sliding window merge
app

Train MMSegmentation GPU
app

Seeds
project

Cats quiz
project