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A small AI tool I built to speed up outfit changes in product photos

Hacker News

A small AI tool I built to speed up outfit changes in product photos

I'm an Amazon seller, not a designer. One thing that kept slowing me down was making small, repetitive changes to product photos—mainly swapping outfits or variants. Photoshop can do it, but for this kind of work it felt heavy. A simple change often turned into a lot of clicking, masking, and exporting. Like most people, I'd already tried using ChatGPT and other image tools for this, but they didn't fit well into a repeatable product photo workflow. I started experimenting with image models on the side and built a small internal tool to handle these edits more directly. After some trial and error, the results became consistent enough that I actually started using it instead of Photoshop for certain tasks. I cleaned it up a bit and made it public. It's intentionally narrow and not trying to do everything—just focused on speed and reducing friction in a workflow I deal with almost every day. Link: https://aiclotheschanger.net Happy to hear feedback, especially from people who spend a lot of time dealing with product images.

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: model, models, chatgpt · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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