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Modern Training Data platform for machine learning delivered as a single application.
Open Source Data Labeling, Workflow, Automation, Exploring, Streaming, and so much more!
Watch a high level video explanation.
Box, Polygons, Lines, Keypoints, Classification Tags, Quadratic Curves, Cuboids, Segmentation, and More
Long, High Frame Rate, High Resolution Videos.
Named Entity Recognition, Part of Speech Tagging, Coreference Resolution, Dependency Parsing
Annotate Audio Regions available now,
Audios Transcription (coming soon)
Support for COG (Cloud Optimized GeoTIFF), streaming, multi-layer, standard and cloud-optimized.
Alpha Release: Geospatial labeling docs
Build your own UI or contact us. Our intent is to build and cover all major media types in 2022, including timeseries, DICOM, and more.
Manage multiple Schemas, Users, Datasets, Process, and so much more.
Organize and surface your machine learning processes. From start, through pre-label ingestion, multiple task stages, training, and back again. Process Manager coming May 2022.
With Diffgram you can get the exact branded experience you want through the what-you-see-is-what-you-get editor. Whitelabel UI Layout & Branding, Automations, Schema, Geometry, Processes, Pipelines, Queries, and More. Diffgram is the most customizable training data platform. Training Data Customization
How secure is your training data? Learn more about Cybersecurity for Training Data
Are you getting great value from Labelbox? Labelbox vs Diffgram
One Click Migration from Labelbox
Learn about upgrading to Diffgram
Contact us to request prioritization of the automatic migration.
Training Data is the art of supervising machines through data. This includes the activities of annotation, which produces structured data; ready to be consumed by a machine learning model. Annotation is required because raw media is considered to be unstructured and not usable without it. That’s why training data is required for many modern machine learning use cases including computer vision, natural language processing and speech recognition.
Diffgram is multiple training data tools in one single application.
- Ingest - Magic Mapping Wizard, High QPS Ingest, All-Cloud File Browser, and More.
- Store - Source of Truth for Training Data, Query at the Source
- Workflow - Human Tasks, Many Many QA Features.
- Annotation - Image, Video, 3D Labeling, Text, Geo, Audio. More Coming.
- Annotation Automation - Customizable, Powerful
- Stream to Training - Direct to PyTorch & Tensorflow Memory
- Explore - Query & Visually See Annotations
- Debug - Compare Models & More
- Secure and Private
Diffgram is Open Source and optionally Client Installed. Quickstart
- Who is Diffgram for?
- Why Diffgram?
- What are Diffgram's competitive advantages?
- Roadmap
- Features
- Standard Features
- Built for Scale
Data Scientists, Machine Learning Leaders, AI Experts, Software Engineers, Data Annotators and Subject Matter Experts.
Learn more about the general concepts with the Training Data Book.
Diffgram brings the functions of a complex toolchain directly into one application. Providing multiple tools with one single integrated application.
Enterprise Questions? Please contact us.
Security issues: Do not create a public issue. Email security@diffgram.com with the details. Docs
Try Diffgram Online (Hosted Service, No Setup.)
Install with Docker and Docker Compose
git clone https://github.com/diffgram/diffgram.git
cd diffgram
pip install -r requirements.txt
python install.py
# Follow the installer instruction and
# After install: View the Web UI at: http://localhost:8085
Read also our Docker compose commands cheat-sheet
If you see any missing features, bugs etc please report them ASAP to diffgram/issues.
See Contribution Guide for more. More on Understanding Diffgram High Level
Full support for Amazon AWS, Google Cloud, and Microsoft Azure.
Run Diffgram on and access data from any of the clouds.
- MinIO
- Google GCP Install Guide Compute Engine
- Azure AKS Kubernetes Install Guide
- AWS Full Kubernetes Guide
- Helm Chart for Kubernetes Clusters
Diffgram is a drop in replacement for the following systems: Labelbox, CVAT, SuperAnnotate, Label Studio (Heartex), V7 Labs (Darwin), BasicAI, SuperbAI, Kili-Technology, Cord, HastyAI, Dataloop, Keymakr, Scale Nucleus.
Please see the roadmap and talk with us if you see a missing feature.
This is an ACTIVE project. We are very open to feedback and encourage you to create Issues and help us grow!
- NEW Streamlined Annotation UI suitable both from "First Time" Subject Matter Experts, and powerful options for Professional Full Time Annotators
- Many User Labeling - Designed for many users from Day 1.
- Scale to Mega Projects with sophisticated organizational concepts.
- Fully configurable - customize labels, attributes, and more.
Ingest prediction data without writing extra scripts.
- NEW Import Wizard saves you hours having to map your data (pre-labels, QA, debug etc.).
- All-Cloud Integrated File Browser
- Scalable pipeline for massive ingestion - we have tested to 600+ hardware nodes
- Integrated pipeline hooks - newly added data auto creates tasks and more
Collaboration across teams between machine learning, product, ops, managers, and more.
- Store virtually any scale of dataset and instantly access slices of the data to avoid having to download/unzip/load.
- Fast access to datasets from multiple machines. Have multiple Data Scientists working on the same data.
- Integrates with your tools and 3rd party workforces. Integrations It's a database for your training data, both metadata and access of raw BLOB data (over top of your storage choice).
Manage Annotation Workflow, Tasks, Quality Assurance and more.
QA Features including:
- QA Slideshow: Reduce Costly Errors
- Reduce Context Switching Costs with Discussions & Issue Tracking
- Get New Team Members Certified with Training and Exams
- Hold People Accountable with Per User Reporting
- Reduce Human Errors with Human Centered Tasks
Learn more -> Quality Assurance Features
- Automatic Per Task Review Routing, with configurable review chance
- Human Task Pipelines.
- Webhooks with Actions
- Easily annotate a single dataset, or scale to hundreds of projects with thousands of subdivided task sets. Includes easy search and filtering.
- Fully integrated customizable Annotation Reporting.
- Continually upgrade your data, including easily adding more depth to existing partially annotated sets.
Fully featured data annotation tool for images and video to create, update, and maintain high quality training datasets.
- Image and Video Annotation.
- Semantic Segmentation Focus Autobordering, turbo mode and more
- Video Annotation High resolution, high frame rate, multiple sequences.
- 3D Annotation (e.g. LiDAR)
Schema (Ontology): Diffgram supports all popular attributes and spatial types including Custom Spatial types. (Best Data Annotation for AI/ML)
Run models instantly with Javascript or make API calls to any language of your choice.
- Automation Examples
- Build your own interactions
- Play with model parameters, and see the results in real time (Coming Soon)
General purpose automation language, solve any annotation automation challenge. Less annotation and automation costs.
Easier and faster for data science. Less compute cost. More privacy controls. Load streaming data from Diffgram directly into pytorch and tensorflow with one line (alpha release live!)
Skip downloading and unzipping massive datasets. Explore data instantly through the browser.
- NEW Data Explorer: Visualize in seconds multiple datasets (Including Video!) and compare models easily without extra computation. Try it now (click Dataset Explorer)
- Automatic Dataset Versioning and user definable datasets.
- Collaborate share and comment on specific instances with a Diffgram Permalink.
Use your models to debug the human. Visually see errors.
Diffgram is an amazing way to access, view, compare, and collaborate on datasets to create the highest quality models. Because these features are fully integrated with the Annotation Tooling, it's absolutely seamless to go from spotting an issue, to creating a labeling campaign, updating schema, etc to correct it.
- Uncover bad data and edge cases
- Curate data and send for labeling with one click
- Automatic error highlighting (Coming Soon)
- Runs on your local system or cloud. Less lag, more secure, more control. Security and Privacy
- Enforce PII & RBAC automatically across life-cycle of training data from ingest to dataset to model predictions and back again (Coming Soon)
Fully integrated automatic test suite, with comprehensive End to End tests and many unit tests.
- Flexible deploy and many integrations - run Diffgram anywhere in the way you want.
- Scale every aspect - from volume of data, to number of supervisors, to ML speed up approaches.
- Fully featured - 'batteries included'.
- Application: Support all popular media types for raw data; all popular schema, label, and attribute needs; and all annotation assist speed up approaches
- Support all popular training data management and organizational needs
- Integrate with all popular 3rd party applications and related offerings
- Support modification of source code
- Run on any hardware, any cloud, and anywhere
Technical Direction - Long Term
Latest AI + More
- Diffgram Python SDK
- Diffgram API Any language
- AWS - Amazon Storage
- GCP Google Storage
- Azure - Now available
- Scale AI
- Labelbox
- Submit a pull request! We want your integration here too
Note for initial open core release Actions Hooks are not yet available. Please see Diffgram.com and use them there if needed.
We welcome contributions! Please see our contributing documentation.
We plan to release more internal architecture docs over time. Please see the general docs in the mean time.
IMPORTANT Disclaimer: Our opinions based on how we define the above categories. Subject to change. A vendor may offer something in one of these categories that doesn’t meet our definition of the category. Some Diffgram checkmarks include items coming soon.