pictograph-io

Pictograph SDK — Productivity skill for Claude Code

Productivity community

Python SDK and CLI for Pictograph: real-time vision tools for agents and developers.

How to install Pictograph SDK

This entry records only its repository, not the path inside it, so there is no exact command to give. Open pictograph-io/pictograph-sdk and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What Pictograph SDK does

Python SDK and CLI for Pictograph: real-time vision tools for agents and developers. SAM3 auto-annotation, RF-DETR and YOLOX training, TensorRT GPU endpoints, live WebRTC/RTSP video streams, tracking and counting workflows.

Alternatives in Productivity

  • Repurpose — Workflow recipe — turn one blog post, video, or idea into a full platform-native content pack (thread, LinkedI 1.3k ★
  • Claude Code Hooks Multi Agent Observability — Real-time monitoring for multi-agent Claude Code sessions via hook event tracking 1.3k ★
  • Pi Subagents — Claude Code like Sub-Agents & Workflow Orchestration for Pi — parallel execution, live widget, fleet view, cus 967 ★

README

Pictograph

Pictograph

Real-time vision tools for agents and developers.

Label images with SAM3, train small task-specific models, and run them in real time:
GPU endpoints, live video streams, and tracking workflows.

[![PyPI](https://img.shields.io/pypi/v/pictograph?color=3e62b0&label=pypi)](https://pypi.org/project/pictograph/) [![Python](https://img.shields.io/pypi/pyversions/pictograph?color=3e62b0)](https://pypi.org/project/pictograph/) [![License](https://img.shields.io/badge/license-MIT-3e62b0)](LICENSE) [![Docs](https://img.shields.io/badge/docs-pictograph.io-3e62b0)](https://pictograph.io/docs)

Docs · Quick start · API reference · App


Four ways in. Same API underneath, so you can move between them.

Python pip install pictograph, this repo
CLI pip install "pictograph[cli]" · reference
REST Any language, X-API-Key header · reference
Claude Code /plugin install pictograph --marketplace pictograph-io/pictograph-sdk · guide

Quick start

pip install pictograph

Upload a directory, draft labels from a text prompt, review them, then export and train.

from pictograph import AnnotateReport, Client, TrainingRun, UploadReport

client = Client()  # reads PICTOGRAPH_API_KEY

uploaded: UploadReport = client.images.upload_from_directory(
    dataset_name="road-signs",
    directory="./road_signs",
)
print(f"{uploaded.images_uploaded} images uploaded")

labelled: AnnotateReport =