DEV Community: Demir Ajvazi

AI Camera — Fan Edition: it hypes up your jersey like a stadium commentator 🏆

Demir Ajvazi — Sun, 12 Jul 2026 00:24:13 +0000

This is a submission for Weekend Challenge: Passion Edition

AI Camera — Fan Edition 🏆📷

What I Built

AI Camera is a phone-camera app that describes what it sees, out loud, in real time — powered by Google's Gemini vision model. It started as an assistive tool for blind and low-vision users (general scene description, reading text aloud, describing an item for a marketplace listing, describing a person's appearance). For this challenge, I added a fifth mode built specifically around passion:

🏆 Fan Mode — point your phone at a jersey, scarf, flag, or any fan gear, and the app turns into a hyped-up stadium commentator, calling out colors, team details, and team spirit with real enthusiasm. With the World Cup happening right now, it felt like the right moment to build it.

📱 Important: this is a mobile-first app. It's built around your phone's rear camera and needs to be held up and pointed at real things — please try it on a phone, not a desktop, for the intended experience.

Demo

🔗 Live app (open on your phone): https://demirajvazi10-max.github.io/ai-camera-fan-edition/

You'll need a free Gemini API key from aistudio.google.com/app/apikey — paste it in when the app asks. It's stored only in your browser and never leaves your device except to call Google's API directly.

(I wasn't able to put together a screen recording for this submission — camera-based apps are a bit awkward to record on a phone! Since the whole thing runs client-side with no backend, the live link above lets you try Fan Mode yourself on your own phone in about 30 seconds.)

Code

https://github.com/demirajvazi10-max/ai-camera-fan-edition

How I Built It

Passion shows up in different ways. Sometimes it's the quiet kind — building something so a person who can't see can still "see" the world around them. Sometimes it's the loud kind — losing your mind over your team's jersey during a World Cup year. I already had the first one built. Adding Fan Mode let the same engine carry both.

Vanilla HTML/CSS/JS — no framework, no build step, no backend
Camera access via getUserMedia, photo captured to a canvas and sent as base64 to the Gemini API (gemini-flash-latest) with a mode-specific prompt
Each mode is just a different prompt string — Fan Mode's prompt asks Gemini to respond "like a hyped-up sports commentator hyping up the crowd"
Responses are read aloud via the browser's Web Speech API (free, works offline once the page is loaded)
The whole thing is one static index.html, so it deploys straight to GitHub Pages with HTTPS — which matters, because phones require a secure context for camera access

Prize Categories

Best Use of Google AI — Gemini's vision model is the core of the app; every one of the five modes depends on it to analyze the photo.

Notes for judges: please test on a phone if possible — that's the intended experience (rear camera + held up to real objects). Fan Mode is the new addition for this challenge; the other four modes existed before as an accessibility tool.

Reviving Ultra Creative Suite: The First Fully Accessible Video Editor for Blind Users

Demir Ajvazi — Sat, 30 May 2026 00:13:16 +0000

This is a submission for the GitHub Finish-Up-A-Thon Challenge

What I Built

Ultra Creative Suite is a professional video and audio editor for Windows, built from the ground up for blind and low-vision users. Every feature works equally for sighted and non-sighted users — no compromises, no stripped-down accessible mode.

I am blind. I use JAWS for Windows daily. I built this because no professional video editor on the market — Adobe Premiere, DaVinci Resolve, Final Cut — is actually usable with a screen reader.

The project includes an AI video generator that takes a single audio file and produces a complete 4K video: lyric analysis, automatic stock footage download, mood-based color grading, ambient sound mixing, and GPU-accelerated rendering.

Demo

GitHub: https://github.com/demirajvazi10-max/Ultra-Creative-suite

The demo video in the repository was created entirely by me — blind, using JAWS only. AI analyzed the lyrics, selected stock footage, applied color grading, mixed ambient sounds, and rendered to 4K. Zero sighted assistance.

The Comeback Story

The project existed and worked, but had several critical issues that made real-world use unreliable:

Before:

Audio fade timing was broken — afade filter used absolute timestamps instead of stream-relative timing, causing ambient sounds to fade incorrectly
totalDuration was not adjusted for AudioStartSeconds, so videos were consistently shorter than expected (2:57 audio rendered as 2:49)
SmartOutroPool had no cap on clip repetition, causing the same outro clip to repeat endlessly
Temp files were written directly to D:\ drive instead of system temp folder, cluttering the disk
IskraSync used incorrect timing references, causing beat-locked edits to drift

After (with GitHub Copilot):

afade now uses st=0 relative to stream start — ambient sounds fade correctly
totalDuration is now corrected immediately after beat detection: rawDuration - AudioStartSeconds
SmartOutroPool has repetition cap, recycle pool, and ultra-safe fallback queries
All temp audio batches now go to %TEMP%\UVE_MixAudio_* with automatic cleanup after render
IskraSync rebuilt to use timelineSpan as primary measure with proper beat-lock offset

GitHub Copilot helped me understand the scope of changes across three files simultaneously and generated a precise commit description that captured every fix — something that would have taken me much longer to write manually while navigating with a screen reader.

My Experience with GitHub Copilot

As a blind developer, navigating code with a screen reader is significantly slower than visual inspection. GitHub Copilot changed my workflow in a concrete way.

When I modified three files — AIVideoCreator.xaml.cs, RenderEngine.cs, and SkiaAnimationEngine.cs — Copilot generated this commit description automatically:

"Multiple fixes across AIVideoCreator, RenderEngine and SkiaAnimationEngine: correct audio fade timing (afade) relative to asetpts/stream start; adjust totalDuration by subtracting AudioStartSeconds so -ss trimming doesn't shorten output unexpectedly; implement SmartOutroPool with max clip duration, recycle pool, ultra-safe fallback queries and fade-out tagging..."

That level of detail would have required me to re-navigate every changed file manually. Copilot gave me that summary instantly, which I could then use directly as a commit message.

For accessibility, this is not a convenience — it is a genuine productivity multiplier.

I'm Blind. I Built a Professional Video Editor. Here's Why.

Demir Ajvazi — Fri, 29 May 2026 12:41:14 +0000

Every time I opened Adobe Premiere, DaVinci Resolve, or any other professional video editor, I hit the same wall. Buttons without labels. Timelines that exist only as visual elements. Drag-and-drop workflows that assume you can see where you're dragging. For a sighted user, these tools are industry standard. For me — a blind developer using JAWS for Windows — they are practically unusable.
I got tired of waiting for someone else to fix this.
So I built Ultra Creative Suite.
What it is
Ultra Creative Suite is a professional video and audio editor for Windows, built from the ground up with one rule: every single feature must work equally for blind, low-vision, and sighted users. No "accessible mode" that hides features. No stripped-down alternative workflow. The same full editor, for everyone.
What it can do
Give it an audio file — a song, a narration, anything — and it will:

Analyze lyrics using a local AI model (Ollama / Qwen 2.5 14B)
Detect mood, season, and energy per lyric line
Automatically download matching stock footage from Pixabay
Apply per-lyric color grading via FFmpeg curves
Mix ambient sounds from a library of 1,279+ categorized clips
Render the finished video to 4K

All of this is controllable entirely through the keyboard. Every action is announced by the screen reader. No mouse required for any core workflow.
The technical decisions that made accessibility possible
The most important decision was the timeline. Most video editors use custom-drawn UI elements for their timelines — visually rich, but completely invisible to screen readers. I used a Win32 native ListView control instead. The same Windows control used in File Explorer. JAWS and NVDA read every clip natively, without plugins or workarounds: clip name, type, duration, position, and AI-generated audio description.
Every dialog has proper focus management. Every action produces a live region announcement. The entire application is navigable with standard keyboard shortcuts.
The demo
The demo video linked in the repository was created entirely by me — blind, using JAWS only. No sighted assistance at any point. AI analyzed the lyrics, selected the footage, applied the effects, mixed the audio, and rendered to 4K. I controlled every step through the keyboard.
Why open source
Because I'm not the only blind developer who has hit this wall. And I'm not the only blind person who wants to create. Ultra Creative Suite is GPL-3, fully open source, and designed to be a reusable foundation for accessible creative software.
If you've ever thought "why isn't there accessible software for X" — maybe this is the starting point.
Links
GitHub: github.com/demirajvazi10-max/Ultra-Creative-suite
If you want to support the project: ko-fi.com/ultra-creativesuite or paypal.me/demirajvazi10