All works

Independent open-source case study

Deep Live Cam Studio

A Windows-focused desktop product evolved from an upstream face-processing project into a more reproducible, hardware-aware release experience for local creative workflows.

Deep Live Cam Studio preview showing a dark desktop interface illustration with CUDA, DirectML, and OBS Live Output labels.
Repository social previewOriginal project artwork by Neil Mitchell
Role
Independent product, release, and engineering work
Evidence snapshot
August 3, 2026
Audited commit
71bb632

Problem

A capable project still needed a dependable Windows release.

The project needed a desktop workflow that could be installed, validated against the intended accelerator, connected to local capture and output, and explained honestly across separate hardware profiles. The delivery problem was to make those capabilities reproducible without obscuring the project's upstream origin.

Measured scope

Evidence, not live counters.

These are fixed results from the published audit snapshot, rather than current GitHub statistics.

authored post-fork commits
158
Since the exact upstream merge base in May 2026.
merged pull requests
20
Release, quality, security, and product work merged into the project.
automated tests
510
Passing source-suite result in the audited repository snapshot.
Windows release profiles
CUDA + DirectML
Separate accelerator distributions with provider-specific validation.

Delivery approach

A release pipeline built around evidence.

The work connects local product behaviour with release engineering, hardware validation, supply-chain evidence, and responsible use.

  1. Product direction

    Shape a Windows desktop experience around local capture, preview, rendering, and virtual-camera output.

  2. Release profiles

    Keep NVIDIA CUDA and AMD or Intel DirectML distributions separate and reproducible.

  3. Evidence gates

    Validate the requested provider in a real ONNX session and pair automation with hardware checks.

  4. Release integrity

    Publish hashes, corresponding source, dependency evidence, and focused release verification.

  5. Responsible use

    Keep models out of release assets and make consent, licence notes, and checksums visible before download.

Evidence snapshot

A measured application growth curve.

Clean application code from the upstream base to the audited snapshot on August 3, 2026.

The visual is an original presentation of the audit data. It measures the maintained product surface, not personal ownership or elapsed effort.

Method

Context makes the measure useful.

Clean application code is measured from tracked Git snapshots and excludes tests, tooling, documentation, licences, binaries, models, and local environments.

The project is a Windows-focused derivative, not a claim of sole authorship. The case study uses original diagrams and a summary of repository evidence only.

Transferable practice

What this demonstrates.

  • 01Delivery planning and dependency management
  • 02Release readiness and operational risk controls
  • 03Technical evidence translated for practical decisions
  • 04Governance, attribution, and open-source stewardship

Attribution and responsible use

Open-source work carries obligations.

Deep Live Cam Studio is a Windows-focused derivative of the original Deep-Live-Cam project. Upstream history and contributors remain part of the project record.

Use face-swap software only with consent and for lawful purposes. This case study describes independent technical work and is not legal advice.

View repository Latest release AGPL-3.0 licence Compliance notes Original project