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A browser-only image processing pipeline inspired by macOS Automator

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A browser-only image processing pipeline inspired by macOS Automator

I’ve been working on a side project for a while and wanted to share it with the HN community to get feedback. The idea started simple: I wanted to do batch image processing entirely in the browser without uploading anything to a server. Most existing tools were either cloud-based (privacy concerns, slow for large batches) or desktop apps that were hard to automate and combine into workflows. A big source of inspiration was macOS Automator. I really liked how you could chain small actions into repeatable workflows, and I wanted something similar for image processing on the web. At first it was just basic operations like crop, resize, compress, and format conversion. Then I kept adding things like: face mosaic face-centered cropping background removal old photo restoration Somewhere along the way it became a full pipeline system that can either run individual steps or chain multiple steps automatically. Everything runs locally in the browser—no server-side processing, no uploads, no data tracking. Technical notes (where I’m unsure) CPU-heavy operations run in WebAssembly Some steps are GPU-accelerated via WebGL Most processing happens off the main thread with OffscreenCanvas + Web Workers A few ML-ish tasks use transformer.js in the browser Next.js is mostly just a UI shell, deployed on Vercel It works, but I’m not sure this is the “right” architecture long-term. Some issues I’ve run into: Memory usage grows fast when chaining multiple steps over large batches Cleaning up intermediate buffers feels fragile Safari behaves very differently from Chromium-based browsers Not sure if Next.js is overkill since everything critical is client-side Questions for HN If anyone here has built heavy client-side tools, I’d love your thoughts on: How to structure long-running pipelines without memory leaks Patterns for cancellation / progress reporting without spaghetti code Whether keeping everything browser-only makes sense Any obvious architectural smells I’m missing I’ve made it a usable tool mainly to test it with real workloads. I’m still iterating, so brutally honest feedback is very welcome.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, apps · Missing: agents, agent, cursor
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Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
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TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal
26%26% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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