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Showing 4 open source projects for "linux live 32"
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Google Cloud’s AI-powered APIs help you translate documents, websites, apps, audio files, videos, and more at scale with best-in-class quality and enterprise-grade control and security.
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CODESOFT is an enterprise-level RFID and barcode label design application offering unmatched flexibility, power, and support. Available in print-only, single-user, and network configurations, CODESOFT is designed to meet all of your barcode labeling needs. Whether your goal is streamlining label printing, printing labels using a form, connecting a scale to your label template, or integrating your business database with your label templates, CODESOFT provides a solution for your organization’s most advanced labeling needs. Connect to SQL or Oracle databases for business system integrations and greater efficiency. CODESOFT includes over 100 barcode symbologies including GS1, supports all common image formats, and enables rich text editing. Native printer drivers are included for over 4,000 thermal, thermal transfer, and inkjet label printers to ensure the best label printing quality.
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Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
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Raster Vision
Open source framework for deep learning satellite and aerial imagery
Raster Vision is an open source framework for Python developers building computer vision models on satellite, aerial, and other large imagery sets (including oblique drone imagery). There is built-in support for chip classification, object detection, and semantic segmentation using PyTorch. Raster Vision allows engineers to quickly and repeatably configure pipelines that go through core components of a machine learning workflow: analyzing training data, creating training chips, training... -
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Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train... -
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Simd
High performance image processing library in C++
... supports following CPU extensions: SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2, AVX, AVX2 and AVX-512 for x86/x64, VMX(Altivec) and VSX(Power7) for PowerPC, NEON for ARM. The Simd Library has C API and also contains useful C++ classes and functions to facilitate access to C API. The library supports dynamic and static linking, 32-bit and 64-bit Windows, Android and Linux, MSVS, G++ and Clang compilers, MSVS project and CMake build systems. -
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