This product was not featured by Product Hunt yet.
It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).

Product upvotes vs the next 3

Waiting for data. Loading

Product comments vs the next 3

Waiting for data. Loading

Product upvote speed vs the next 3

Waiting for data. Loading

Product upvotes and comments

Waiting for data. Loading

Product vs the next 3

Loading

FeatLens

Visualize feature maps from any vision model effortlessly.

Model-agnostic feature-map visualization: PCA-to-RGB feature maps from any vision model and any layer.

Top comment

Feature visualization is part of my daily routine as a computer vision researcher. But doing it across different model providers was always a mess. So this weekend, I finally fixed it 🧩 Every model lives somewhere different, torch.hub, timm, HuggingFace, some random GitHub repo, and each one needs its own glue code just to pull out and visualize feature maps. I got tired of rewriting that glue every single time. 🤖 So I built FeatLens: a model-agnostic framework to see what any vision model actually encodes. 🔹 Load from anywhere — timm, HuggingFace, torch.hub (like V-JEPA), an external repo, or your own nn.Module (yes, CNNs too) 🔹 Any layer, laid out as a clean model × layer grid 🔹 Color the features by PCA, cosine similarity, k-means, foreground, saliency, or attention-rollout 🔹 Match patches across two images, batch a whole folder, or sweep a video clip Just swap the models, and watch the features change completely. It's oddly satisfying to look at. This was a weekend project I built with my friend Claude, from core design to docs, tests, and CI. It's open source, and you can just pip install featlens ⭐ GitHub: https://lnkd.in/dGvb7uNi 📖 Docs: https://lnkd.in/dQMV9-Bc 🤗 Live demo: https://lnkd.in/d6HeRJk6 If it's useful in your work, it's citable, and contributions are very welcome. Which model would you want to peek inside first? 👀

About FeatLens on Product Hunt

Visualize feature maps from any vision model effortlessly.

FeatLens was submitted on Product Hunt and earned 15 upvotes and 7 comments, placing #25 on the daily leaderboard. Model-agnostic feature-map visualization: PCA-to-RGB feature maps from any vision model and any layer.

On the analytics side, FeatLens competes within Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1M followers on Product Hunt. The dashboard above tracks how FeatLens performed against the three products that launched closest to it on the same day.

Who hunted FeatLens?

FeatLens was hunted by Turhan Can KARGIN. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of FeatLens including community comment highlights and product details, visit the product overview.