#cplusplus #deep_learning #inference #inference_engine #openvino #performance

https://github.com/openvinotoolkit/openvino

#jupyter_notebook #computer_vision #deep_learning #inference #machine_learning #openvino

https://github.com/openvinotoolkit/openvino_notebooks

#python #tensorrt #ncnn #onnx #yolov3 #openvino #yolox #yolox_nano

https://github.com/Megvii-BaseDetection/YOLOX

#cplusplus #deployment #model_converter #ncnn #onnxruntime #openvino #pplnn #sdk #tensorrt

https://github.com/open-mmlab/mmdeploy

#python #anomaly_detection #anomaly_localization #anomaly_segmentation #neural_network_compression #openvino #unsupervised_learning

https://github.com/openvinotoolkit/anomalib

#python #caffe #computer_vision #coreml #edgetpu #keras #mediapipe #model #model_zoo #models #onnx #openvino #pretrained_models #pytorch #tensorflow #tensorflow_lite #tensorflowjs #tf_trt #tfjs #tflite #tflite_models

https://github.com/PINTO0309/PINTO_model_zoo

#cplusplus #android #deep_learning #deployment #graphcore #intel #ios #jetson #kunlun #object_detection #onnxruntime #openvino #picodet #rockchip #sdk #serving #tensorrt #uie #yolov5

https://github.com/PaddlePaddle/FastDeploy

#python #chineseocr #crnn #dbnet #easyocr #ocr #onnxocr #onnxruntime #openvino #paddleocr #rapidocr

RapidOCR is a free, open-source tool that quickly recognizes text from images. It is very fast, supports multiple languages like Chinese and English, and works on various platforms including Linux, Windows, and Mac. You can use it offline, which is convenient. The tool is easy to install and use, and it even allows you to customize it for specific needs. This makes it beneficial for users who need quick and accurate text recognition without relying on internet connectivity.

https://github.com/RapidAI/RapidOCR

#jupyter_notebook #computer_vision #deep_learning #inference #machine_learning #openvino

OpenVINO Notebooks are a collection of interactive Jupyter notebooks that help developers learn and experiment with the OpenVINO Toolkit. These notebooks provide an introduction to OpenVINO basics and show how to optimize deep learning inference using the API. They can be run on various platforms, including Windows, Ubuntu, macOS, and cloud services like Azure ML or Google Colab. This makes it easy for users to get started with AI development without needing extensive hardware knowledge, allowing them to focus on building applications efficiently across different devices.

https://github.com/openvinotoolkit/openvino_notebooks

#python #agents #generative_ai_tools #llamacpp #llm #onnx #openvino #parsing #retrieval_augmented_generation #small_specialized_models

llmware is a powerful, easy-to-use platform that helps you build AI applications using small, specialized language models designed for business tasks like question-answering, summarization, and data extraction. It supports private, secure deployment on your own machines without needing expensive GPUs, making it cost-effective and safe for enterprise use. You can organize and search your documents, run smart queries, and combine knowledge with AI to get accurate answers quickly. It also offers many ready-to-use models and examples, plus tools for building chatbots and agents that automate complex workflows. This helps you save time, improve accuracy, and securely leverage AI for your business needs[1][3][5].

https://github.com/llmware-ai/llmware