February 16, 2026
Email walls get smashed
Show HN: I generated a "stress test" of 200 rare defects from 7 real photos
Cool broken-parts pics, uncool sign-up—HN wins free link
TLDR: A dev shared 200 synthetic “broken insulator” images to stress-test image recognition, but a sign-up gate drew backlash. He quickly apologized and posted a direct free link, turning the debate into a win for open access and better testing of rare failures.
Hacker News lit up when a builder dropped a shiny set of 200 synthetic pics of broken electrical insulators—crafted from just seven real defects—to help teams stress‑test image recognition. Folks loved the goal (rare failures are notoriously hard to catch), but the CC0 “free” release arrived behind an email sign‑up and credits gate. Cue outrage: “It’s not free if we have to trade our info,” grumbled the crowd, while others warned gating would just push people to rehost. The set, meant for validation (a real‑world check, not training), suddenly looked less like a gift and more like an “email trap.”
Then the plot twist: the creator popped back with a swift “My bad” and a direct Huggingface link. Mood swing! Pitchforks down, bookmarks up. Commenters joked the real “rare defect” wasn’t the broken insulators—it was the sign‑up wall—and christened the thread “free as in download.” Beyond the drama, consensus landed here: 200 labeled images help teams measure recall (how many misses you actually catch) on those “one‑in‑10,000” edge cases before shipping. Hot take of the day? Synthetic won’t replace real, but it makes testing way less terrifying. Verdict: cool dataset, and thanks for removing the gatekeeper.
Key Points
- •The author built a pipeline to generate synthetic variations of rare defects from seven real samples.
- •A CC0 “broken insulators” dataset of 200 images is released for validation/testing, not full training.
- •The images include varied lighting and backgrounds to create hard-to-detect scenarios.
- •All images are fully labeled in COCO and YOLO formats for object detection evaluation.
- •The goal is to benchmark and improve recall on rare failure modes in structural inspection systems.