autoneat

Standalone Neat Video Pro 6 Auto Profile automation for DaVinci Resolve.

Neat Video has no public scripting API for Auto Profile. autoneat scripts the parts Resolve exposes, then uses macOS window automation, OCR, and learned OpenCV templates for the controls Neat does not expose: Auto Profile and Apply.

Install

python3 -m pip install autoneat

DaVinci Resolve Studio, Neat Video Pro 6, macOS Accessibility / Screen Recording permissions, and Tesseract OCR are required. Run:

autoneat doctor

CLI

Run against the current Resolve project/timeline:

autoneat profile

Run against a specific project/timeline and shot filter:

autoneat profile \
  --shot-ids 001 002 003 \
  --continue \
  --retry-failed

Important options:

--continue resumes from the state JSON.
--retry-failed retries previously failed clips when resuming.
--all-video-tracks processes all video tracks instead of --track 1.
--fresh-neat adds a fresh Neat node instead of reusing one.
--reset deletes existing Neat nodes and rebuilds from scratch.
--color-wrap enables the HDR/linear ColorSpaceTransform wrapper.
--no-templates disables learned OpenCV templates and uses OCR only.
--json prints the final summary object after the live log.

Python API

from autoneat import ProfileOptions, run_profile

result = run_profile(
    ProfileOptions(
        project_name="My Show",
        timeline_name="My Show_Neat",
        shot_ids=["001", "002"],
    )
)

How It Works

For each selected timeline clip, autoneat:

Moves the Resolve playhead to the clip.
Adds or reuses the Neat Video OFX node.
Wraps ACES/HDR clips with ColorSpaceTransform nodes so Neat sees display-referred pixels.
Opens Neat via the OFX Prepare Profile___ button control.
OCR-clicks Auto Profile, waits for readiness, then OCR-clicks Apply.
Writes a state JSON after every clip for resumable batches.

Development

python3 -m venv .venv
./.venv/bin/python -m pip install -e ".[test]"
./.venv/bin/python -m pytest

License

MIT.

Release files for autoneat 0.4.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for autoneat 0.4.7
File	Size	Uploaded
autoneat-0.4.7.tar.gz	94.8 kB	Jun 30, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for autoneat 0.4.7
File	Interpreter	ABI	Platform	Reset
autoneat-0.4.7-py3-none-any.whl 99.0 kB Jun 30, 2026	Python 3	none	any	Details

Total release size: 193.9 kB

Release files / autoneat-0.4.7.tar.gz

Download URL	autoneat-0.4.7.tar.gz
Size	94.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`f0c008adb80a288507d7d73935d72d0b3f59dafe3955d72180f05f8fcc7df558`
BLAKE2b-256 checksum How to use checksums	`7f8b2b0b8f85c23d6ee80e2224677fca616fb6dd4b7a0a45a3db53af508930d1`
Upload date	Jun 30, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.12`

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Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/mhadifilms/autoneat
Publishing commit: github.com/mhadifilms/autoneat/tree/73f1d42c886ab3a138ca117b377512690bd4c491

Workflow

Publishing configuration: github.com/mhadifilms/autoneat/blob/73f1d42c886ab3a138ca117b377512690bd4c491/.github/workflows/pypi.yml
Publishing logs: github.com/mhadifilms/autoneat/actions/runs/28465478371/attempts/1

Artifact

Subject: autoneat-0.4.7.tar.gz
SHA-256 checksum: f0c008adb80a288507d7d73935d72d0b3f59dafe3955d72180f05f8fcc7df558 Verifying attestations

Release files / autoneat-0.4.7-py3-none-any.whl

Download URL	autoneat-0.4.7-py3-none-any.whl
Size	99.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`3f95ab52d598e6bf0d42353b431c36f5edb04d8e6cfbbddb5e62b9e96eee5793`
BLAKE2b-256 checksum How to use checksums	`bd40bfb856e6536a1765068e160052f2f3a7f5e946eb030887d370414d8c1455`
Upload date	Jun 30, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.12`

Provenance

Identity

Publishing platform: GitHub Actions
Publishing repository: github.com/mhadifilms/autoneat
Publishing commit: github.com/mhadifilms/autoneat/tree/73f1d42c886ab3a138ca117b377512690bd4c491

Workflow

Publishing configuration: github.com/mhadifilms/autoneat/blob/73f1d42c886ab3a138ca117b377512690bd4c491/.github/workflows/pypi.yml
Publishing logs: github.com/mhadifilms/autoneat/actions/runs/28465478371/attempts/1

Artifact

Subject: autoneat-0.4.7-py3-none-any.whl
SHA-256 checksum: 3f95ab52d598e6bf0d42353b431c36f5edb04d8e6cfbbddb5e62b9e96eee5793 Verifying attestations