Computer vision
that runs itself.
The platform to annotate, train, and deploy computer vision workflows that run on a schedule. From solo devs to enterprise teams.
$5/mo free compute. No payment method required.
from pictograph import Client, TrainingRun
client = Client()
# Freeze the dataset, then train RF-DETR on a managed GPU
client.exports.create(
dataset_name="Doorbell Camera",
name="v1",
format="coco",
)
run: TrainingRun = client.training.create(
dataset_name="Doorbell Camera",
export_name="v1",
pipeline_type="rfdetr_segmentation",
name="doorbell-seg",
gpu_type="a100",
config={"epochs": 15},
)Featured public datasets
from pictograph import Client, PromptResult
client = Client()
# Label from a text prompt. No training required.
result: PromptResult = client.auto_annotate.text(
dataset_name="road-signs",
image_filename="img-001.jpg",
text_prompt="stop sign",
)
client.annotations.save(
dataset_name="road-signs",
image="img-001.jpg",
annotations=result.annotations,
)Label with a click, a box,
or a prompt
SAM3 turns a point, a box, or a text prompt into pixel-perfect labels. Annotate one image, or run a batch over thousands.
from pictograph import Client, TrainingRun
client = Client()
# Freeze the dataset into an export, then train on it
client.exports.create(
dataset_name="road-signs",
name="v1",
format="coco",
)
run: TrainingRun = client.training.create(
dataset_name="road-signs",
export_name="v1",
pipeline_type="rfdetr_detection",
name="signs-detector",
config={"epochs": 30},
)
client.training.wait_for_completion(run_id=run.id)Train vision models
without the infrastructure
Pick an architecture and a GPU. Pictograph exports your data, trains on managed GPUs, and returns model weights.
from pictograph import Client, DeploymentClient, CreatedDeployment
client = Client()
# Stand a trained model up as an always-on endpoint
created: CreatedDeployment = client.deployments.create(
model="signs-detector",
gpu_type="t4",
)
# Call /predict directly. Billed by uptime.
endpoint = DeploymentClient(
endpoint=created.deployment.endpoint_url,
api_key=created.auth_token,
)
print(endpoint.infer(image="./frame.jpg").predictions)Deploy custom models
with one click
Turn a trained model into an authenticated /predict endpoint. Call it from REST, the SDK, or the CLI. Billed by uptime, paused anytime.
from pictograph import Client, WorkflowRun
client = Client()
# Run a saved workflow. Its graph lives in the app.
created = client.workflows.run(workflow="people-counter")
result: WorkflowRun = client.workflows.wait_for_run(
run_id=created.run_id,
)
print(result.step_results) # counts, dwell, occupancyRun pipelines
over images and video
Build a pipeline in a visual editor and run it over images or video. Track objects, count crossings, and measure dwell time.
Everything else you need
Import and export anywhere, search your library, and drive it all from the SDK, CLI, or an agent.
Multi-format export
COCO, YOLO, CVAT, Pascal VOC, LabelMe, CSV, or Pictograph JSON.
Dataset connectors
Import existing datasets from V7 (Darwin) and Roboflow in a few clicks.
Webhooks
Signed, retried event delivery you can replay anytime.
Explore
A public hub of datasets and models. Star, comment, and fork into your workspace.
Team workspaces
Role-based access for owner, admin, member, and viewer across your organization.
Python SDK + CLI
A typed Python client with auto-retry. pip install pictograph.
Agent-ready
Drive every operation from Claude or OpenAI through the 37-tool registry.
Visual search
Search by visual similarity, or by the objects and scenes detected in every image.
Start building today
$5/mo free compute. No payment method required.