Search Results for "image processor"
Sort By:
Showing 10 open source projects for "image processor"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
1
GenAI Processors
GenAI Processors is a lightweight Python library
GenAI Processors is a lightweight Python library for building modular, asynchronous, and composable AI pipelines around Gemini. Its central abstraction is the Processor, a unit of work that consumes an asynchronous stream of parts (text, images, audio, JSON) and produces another stream, making it natural to chain operations and keep everything streaming end-to-end. Processors can be composed sequentially (to build multi-step flows) or in parallel (to fan-out work and merge results), which... -
2
Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It... -
3
Jittor
Jittor is a high-performance deep learning framework
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement... -
4
openWrt-snort
Image of OpenWrt OS, with snort community featured in.
Image of OpenWrt OS, with snort community featured in, for Raspberry Pi 4/ 4B+ and 400, basically for Processor BCM2711. Installed Snort Community Model to Intrusion Detection system. Prevention system not installed. eth0 used as output/ LAN socket, to run internet and access router. eth1, which can be USB -> Ethernet port, is used as WAN port, to connect Pi board to Internet IP. -
Atera - an All-in-one platform for IT managementYour IT essentials, integrated & elevated. Take your IT management from automated to autonomous, download Atera's agent to start your free trial!
-
5
SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
...Amazon SageMaker uses Docker containers to run all training jobs and inference endpoints. The Docker images are built from the Dockerfiles in docker/. The Dockerfiles are grouped based on the version of TensorFlow Serving they support. Each supported processor type (e.g. "cpu", "gpu", "ei") has a different Dockerfile in each group. If your are testing locally, building the image is enough. But if you want to your updated image in SageMaker, you need to publish it to an ECR repository in your account. You can also run your container locally in Docker to test different models and input inference requests by hand. -
6
BerryNet
Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events... -
7
IMAGINE
Biological image viewer and processor
Detection, enumeration, and sizing of biological organisms by image analysis. -
8
ctqa-cp
Automatic analysis of CT images of the CatPhan600/504 phantom
Hosted at google code, for latest version please go to: https://code.google.com/p/ctqa-cp/ Automatic image quality analysis of computed tomography images of the CatPhan? phantom. CTQA is a software package to aid in quality assurance of image quality for CT scanners. The software currently only supports analysis of CT-images of the CatPhan600? phantom. Other phantoms may be supported upon request. The purpose of CTQA-cp is twofold: 1) To handle and analyze image sets consisting of a few thousand images that is commonly obtained from image quality assurance protocols on CT scanners. 2) Easily provide results that can be copied to your favorite word or spreadsheet processor, or be saved to disk. -
9
GTKRawGallery is a workflow oriented photo retouching software for camera raw image development. It is also a versatile photo manager for popular image formats.
-
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
-
10
Batch Image Processor This simple Command line utility allows you to process (ie scale, rotate, change format/quality) a collection of image files. This arose from my need to find a simple way to reduce photos for emailing to family and friends.
- Previous
- You're on page 1
- Next
