DSLR Control MVP with AI
Budget: $1,500 – $3,000 USD
I need a proof-of-concept Windows desktop app that can take over a Nikon DSLR connected by USB, trigger photo or short-video capture, pipe the footage through an AI background-replacement service, then present the finished result in a full-screen, touchscreen-friendly interface.
Core flow
1. Control a Nikon body using the official SDK (or a reliable open-source wrapper).
2. Capture single images and up to 30-second clips.
3. Immediately send the raw file to an AI endpoint. I have access to both OpenAI and Stable Diffusion APIs and I’m open to your recommendation on which is faster and more cost-effective for real-time background/scene generation.
4. Show the composited output in a simple gallery view where users can swipe through, accept or discard.
5. On acceptance, allow export to a local folder and auto-generate a QR code that points to the saved file for easy mobile download.
Tech stack is flexible: Python (PyQt, Kivy), C# (.NET/WPF), or Electron—choose whatever gets us to a stable MVP quickest, as long as setup on Windows is straightforward. As part of the delivery I’ll need:
• Well-commented source code and build/run instructions
• A brief README describing any third-party libraries, API keys, or SDK installers required
• A short screen-capture video showing the full capture-to-export sequence
If something in the scope feels unclear, flag it early so we can keep the prototype tight and focused.
Core flow
1. Control a Nikon body using the official SDK (or a reliable open-source wrapper).
2. Capture single images and up to 30-second clips.
3. Immediately send the raw file to an AI endpoint. I have access to both OpenAI and Stable Diffusion APIs and I’m open to your recommendation on which is faster and more cost-effective for real-time background/scene generation.
4. Show the composited output in a simple gallery view where users can swipe through, accept or discard.
5. On acceptance, allow export to a local folder and auto-generate a QR code that points to the saved file for easy mobile download.
Tech stack is flexible: Python (PyQt, Kivy), C# (.NET/WPF), or Electron—choose whatever gets us to a stable MVP quickest, as long as setup on Windows is straightforward. As part of the delivery I’ll need:
• Well-commented source code and build/run instructions
• A brief README describing any third-party libraries, API keys, or SDK installers required
• A short screen-capture video showing the full capture-to-export sequence
If something in the scope feels unclear, flag it early so we can keep the prototype tight and focused.