vizion3d

vizion3d is an open-source Python library for 3D computer vision that gives ML/CV researchers a single, unified interface for running inference across the full spectrum of 3D vision tasks — from depth estimation and point cloud generation to NeRF reconstruction and pose estimation.

Every task is accessible through three consumption modes driven by one shared CQRS architecture:

Mode	When to use
Direct Python import	Notebooks, research scripts, local prototyping
REST API	Web integrations, any-language clients
gRPC API	High-throughput, low-latency microservice pipelines

---

Installation

Requires Python 3.12 (Open3D constraint).

PyTorch is not bundled in the base install — choose the extra that matches your hardware (see Hardware Acceleration). For most users the cpu extra is the right default; it installs the standard PyTorch wheel which covers CPU, NVIDIA CUDA, and Apple Silicon MPS automatically.

pip

pip install "vizion3d[cpu]"

Poetry

poetry add "vizion3d[cpu]"

uv

uv python pin 3.12
uv add "vizion3d[cpu]"

---

Hardware acceleration

vizion3d detects the best available backend automatically at runtime — no code changes required. Supported backends are CPU, NVIDIA CUDA, Apple Silicon MPS, and AMD ROCm.

For per-backend prerequisites, install commands, and platform notes, see the Hardware Acceleration page.

---

Quick start — depth estimation

Get a depth map and point cloud from a single image in under 10 lines.

import open3d as o3d
from vizion3d.lifting import DepthEstimation, DepthEstimationCommand

result = DepthEstimation().run(
    DepthEstimationCommand(
        image_input="scene.png",
        return_point_cloud=True,
    )
)

print(f"Depth range : {result.min_depth:.4f} → {result.max_depth:.4f}")
print(f"Points      : {len(result.point_cloud.points)}")
print(f"Scale       : {result.point_cloud_scale} metre per unit")

o3d.io.write_point_cloud("scene.ply", result.point_cloud)

---

Starting the servers

pip / Poetry

# REST API (FastAPI, default port 8000)
vizion3d-serve-rest

# gRPC API (default port 50051)
vizion3d-serve-grpc

uv

# REST API (FastAPI, default port 8000)
uv run vizion3d-serve-rest

# gRPC API (default port 50051)
uv run vizion3d-serve-grpc

---

Architecture

vizion3d uses a CQRS pattern throughout:

• Commands carry inference parameters and trigger side-effecting handlers.
• Queries retrieve results or metadata without side effects.
• All handlers are registered through a clean_ioc container — no direct handler instantiation anywhere in the public API.

Each task lives in its own module under vizion3d/<category>/ and exposes exactly commands.py, handlers.py, and models.py. Adding a new task means adding one module and one container registration — nothing else changes.

---

Tasks

Lifting (2D → 3D)

Task	Status	Docs
Monocular depth estimation	Stable	Depth Estimation
Stereo depth estimation	Stable	Stereo Depth