The model is only available in AI Studio when I set my VPN to the USA (I’m located in the UK).
Readit Newssimedw commented on Gemini 2.5 Flash Image developers.googleblog.com... · Posted by u/meetpateltech
simedw commented on Is Gemini 2.5 good at bounding boxes? simedw.com/2025/07/10/gem... · Posted by u/simedw
A detail that is not mentioned is that Google models >= Gemini 2.0 are all explicitly post-trained for this task of bounding box detection: https://ai.google.dev/gemini-api/docs/image-understanding
Given that the author is using the specific `box_2d` format, it suggests that he is taking advantage of this feature, so I wanted to highlight it. My intuition is that a base multimodal LLM without this type of post-training would have much worse performance.
That's true, it's also why I didn't benchmark against any other model provider.
It has been tuned so heavily on this specific format that even a tiny change, like switching the order in the `box_2d` format from `(ymin, xmin, ymax, xmax)` to `(xmin, ymin, xmax, ymax)` causes performance to tank.
simedw commented on Is Gemini 2.5 good at bounding boxes? simedw.com/2025/07/10/gem... · Posted by u/simedw
I wrote a similar article a couple of months ago, but focusing instead on PDF bounding boxes—specifically, drawing boxes around content excerpts.
Gemini is really impressive at these kinds of object detection tasks.
https://www.sergey.fyi/articles/using-gemini-for-precise-cit...
That's really interesting, thanks for sharing!
Are you using that approach in production for grounding when PDFs don't include embedded text, like in the case of scanned documents? I did some experiments for that use case, and it wasn't really reaching the bar I was hoping for.
simedw commented on Is Gemini 2.5 good at bounding boxes? simedw.com/2025/07/10/gem... · Posted by u/simedw
Really interesting piece, the bit about tight vs loose bounding boxes got me thinking. Small inaccuracies can add up fast, especially in edge cases or when training on limited data.
Has anyone here found good ways to handle bounding box quality in noisy datasets? Do you rely more on human annotation or clever augmentation?
Thank you! Better training data is often the key to solving these issues, though it can be a costly solution.
In some cases, running a model like SAM 2 on a loose bounding box can help refine the results. I usually add about 10% padding in each direction to the bounding box, just in case the original was too tight. Then if you don't actually need to mask you just convert it back to a bounding box.
simedw commented on Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages simedw.com/2025/06/23/int... · Posted by u/simedw
Which it apparently does by completely changing the recipe in random places including ingredients and amounts thereof. It is _indeed_ a very good microcosm of what LLMs are, just not in the way these comments think.
It was actually a bit worse than that the LLM never got the full recipe due to some truncation logic I had added. So it regurgitated the recipe from training, and apparently, it couldn't do both that and convert units at the same time with the lite model (it worked for just flash).
I should have caught that, and there are probably other bugs too waiting to be found. That said, it's still a great recipe.
simedw commented on Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages simedw.com/2025/06/23/int... · Posted by u/simedw
Changes Spegel made to the linked recipe's ingredients:
Pounds of lamb become kilograms (more than doubling the quantity of meat), a medium onion turns large, one celery stalk becomes two, six cloves of garlic turn into four, tomato paste vanishes, we lose nearly half a cup of wine, beef stock gets an extra ¾ cup, rosemary is replaced with oregano.
Fantastic catch! It led me down a rabbit hole, and I finally found the root cause.
The recipe site was so long that it got truncated before being sent to the LLM. Then, based on the first 8000 characters, Gemini hallucinated the rest of the recipe, it was definitely in its training set.
I have fixed it and pushed a new version of the project. Thanks again, it really highlights how we can never fully trust models.
simedw commented on Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages simedw.com/2025/06/23/int... · Posted by u/simedw
simedw commented on Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages simedw.com/2025/06/23/int... · Posted by u/simedw
It would be cool of it were smart enough to figure out whether it was necessary to rewrite the page on every visit. There's a large chunk of the web where one of us could visit once, rewrite to markdown, and then serve the cleaned up version to each other without requiring a distinct rebuild on each visit.
If the goal is to have a more consistent layout on each visit, I think we could save the last page's markdown and send it to the model as a one-shot example...
simedw commented on Show HN: Spegel, a Terminal Browser That Uses LLMs to Rewrite Webpages simedw.com/2025/06/23/int... · Posted by u/simedw
In your cleanup step, after cleaning obvious junk, I think you should do whatever Firefox's reader mode does to further clean up, and if that fails bail out to the current output. That should reduce the number of tokens you send to the LLM even more
You should also have some way for the LLM to indicate there is no useful output because perhaps the page is supposed to be a SPA. This would force you to execute Javascript to render that particular page though
Just had a look and three is quite a lot going into Firefox's reader mode.