Alternatives
Products that do what MoonVision does
Dear HN, this is Alex, cofounder of Moonvision, an Austrian based computer vision company. We started in 2017 tracking grilled chicken at the Oktoberfest Munich [1] and transitioned into automating visual inspections tasks. Our web tools are used by quality assurance experts to manage training data and create custom models without an external workforce. For such tasks and experts, the effort to label data is often prohibitive. Therefore, we built tools that work with low amounts of initial data. To train a new pipeline we cover the following 6 steps: - Video gathering - Object mining -…
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Starting today, DirectAI’s Zero-Shot Image Classification & Object Detection APIs are public. Define classes and objects exclusively in natural language - no training data required. And if something goes wrong, you can resolve the edge case in natural language too! We’ve been hard at work to bring powerful and controllable computer vision to everybody. To do this, we’re building novel ways of interacting with the knowledge stored in large foundation models. We’re bootstrapping from zero-shot methods to create new approaches that allow for more control over decision boundaries, without…
2023 · github.com
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2020 · github.com
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I've been working on training this small vision language model for the last month - excited to release the first prototype today! It is based on SigLIP (image encoder), Phi-1.5 (text model) and trained using the LLaVa-1.5 training dataset. It runs reasonably fast on CPU with ~8GB of RAM in full 32-bit precision. There's plenty of room to speed it up and reduce memory consumption by quantizing the model. I posted a video of it running on my M2 Macbook Air (on CPU not MPS, so performance should be comparable on other hardware) on Twitter to demonstrate inference speed:…
2023 · github.com
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supervision is a Python package with tools for building computer vision applications. With supervision, you can: - Load and filter predictions from a range of state of the art models into a standard API (i.e. YOLOv8, SAM). - Annotate images and videos with bounding boxes, segmentation masks, and more. - Calculate confusion matrices. - Use ByteTrack to track objects. - Use SAHI to process small object detection. - Process video frames. - And more. Our goal with supervision is to provide model-agnostic tools with a concise syntax that you can use to build logic on top of computer vision…
2023 · github.com
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2014 · obvious.io
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Hello HN! I'm an Android OS engineer. I've worked with AOSP and Linux kernels all my career and always wondered about lack of sophisticated tools to debug and analyze system-level logs. Always had to resort to manually skimming through large log files to find something I needed to. With the rise of LLMs and the AI-age, I felt it was a great opportunity to build something for OS engineers, which is what led to logcat.ai! We are building the industry-first observability platform for system level intelligence. Think "Datadog for operating systems" instead of applications. Currently, we support…
2025 · logcat.ai
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I wrote up a retrospective on my time working as a founder at DirectAI (https://directai.io). We learned a lot and I wanted to share some things I wish I had known ~18 months ago.
2024 · brooks.team
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