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Auto-optimize and upload images with AI alt text

Hacker News

Auto-optimize and upload images with AI alt text

I've been manually optimizing images for web projects by resizing, converting formats, uploading to S3, and writing alt text. Built this project to automate the whole pipeline, and wanted to open source it for the community. What it does: - Analyzes images and picks optimal format (WebP/JPEG/PNG) based on content - Batch processes from CSV or local files - Generates alt text via AltText.ai API - Uploads to S3 with CloudFront URLs - Includes REST API for integration The format detection compares output sizes across formats, rather than relying on file extension rules. Saves significant bandwidth - saw 40-60% size reductions on most images. Also built an enhanced pre-commit script that auto-fixes linting issues and updates vulnerable dependencies. Setup: Clone repo, run setup script, add AWS creds. No external dependencies beyond AWS and optional AltText.ai API. Includes example files. Would appreciate feedback on the format selection algorithm or suggestions for additional optimizations.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, pipe, io · Missing: https docs, excited, just released
17%17% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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