#jupyter_notebook #coreml #ios #object_detection #onnx #pytorch #tflite #yolov3 #yolov4 #yolov5

https://github.com/ultralytics/yolov5

#cplusplus #cpp #deep_learning #machine_learning #ml #neural_network #onnx

https://github.com/neoml-lib/neoml

#python #darknet2onnx #darknet2pytorch #onnx #pytorch #pytorch_yolov4 #tensorrt #yolov4

https://github.com/Tianxiaomo/pytorch-YOLOv4

#javascript #ai #caffe #caffe2 #coreml #darknet #deep_learning #deeplearning #keras #machine_learning #machinelearning #ml #mxnet #neural_network #onnx #paddle #pytorch #tensorflow #tensorflow_lite #torch #visualizer

https://github.com/lutzroeder/netron

#python #nlp #sparsity #tensorflow #keras #pytorch #deep_learning_algorithms #image_classification #deep_learning_library #pruning #object_detection #automl #computer_vision_algorithms #onnx #deep_learning_models #sparsification #pruning_algorithms #smaller_models #model_sparsification #sparsification_recipes #recipe_driven_approaches

https://github.com/neuralmagic/sparseml

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

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

#python #ai #artificial_intelligence #computer_vision #coreml #deep_learning #high_resolution #machine_learning #matting #onnx #pytorch #real_time #tensorflow #tfjs #video_matting

https://github.com/PeterL1n/RobustVideoMatting

#scala #ai #apache_spark #azure #big_data #cognitive_services #data_science #databricks #deep_learning #http #lightgbm #machine_learning #microsoft #ml #model_deployment #onnx #opencv #pyspark #spark #synapse

https://github.com/microsoft/SynapseML

#python #detection #detextron2 #detr #face #instance_segmentation #object_detection #onnx #tensorrt #transformers #yolo #yolov6 #yolov7 #yolox

https://github.com/jinfagang/yolov7

#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

#python #anchor_free #computer_vision #deep_learning #edge_computing #object_detection #object_detector #onnx #pytorch #tensorrt #yolo

https://github.com/LSH9832/edgeyolo

#python #damo_yolo #deep_learning #imagenet #nas #object_detection #onnx #pytorch #tensorrt #yolo #yolov5

https://github.com/tinyvision/DAMO-YOLO

#python #graphcore #habana #inference #intel #onnx #onnxruntime #optimization #pytorch #quantization #tflite #training #transformers

https://github.com/huggingface/optimum

#python #onnx #pytorch #voice_activity_detection #voice_commands #voice_control #voice_detection #voice_recognition

https://github.com/snakers4/silero-vad

#python #coreml #deep_learning #ios #machine_learning #ml #object_detection #onnx #pytorch #tflite #ultralytics #yolo #yolov3 #yolov5

YOLOv5 is a powerful and easy-to-use AI model for object detection, image segmentation, and classification. It is designed to be fast, accurate, and simple to implement. Here are the key benefits YOLOv5 is straightforward to set up and use, with detailed documentation and tutorials available.
- **Performance** You can use YOLOv5 for object detection, image segmentation, and classification tasks.
- **Community Support** You can run YOLOv5 in various environments such as Google Colab, Paperspace, Kaggle, and Docker.

Overall, YOLOv5 simplifies the process of integrating advanced AI capabilities into your projects.

https://github.com/ultralytics/yolov5

#cplusplus #ai_framework #deep_learning #hardware_acceleration #machine_learning #neural_networks #onnx #pytorch #scikit_learn #tensorflow

ONNX Runtime is a tool that makes machine learning faster and cheaper. It works on many different devices and operating systems, like Windows, Linux, and Mac, and supports popular machine learning frameworks like PyTorch and TensorFlow. This means you can use it to speed up your machine learning models, making your applications run faster and more efficiently. It also helps in training models quickly, especially on powerful NVIDIA GPUs. This benefits you by providing faster customer experiences and lower costs for your machine learning projects.

https://github.com/microsoft/onnxruntime

#cplusplus #aarch64 #android #arm32 #asr #cpp #csharp #dotnet #ios #lazarus #linux #macos #mfc #object_pascal #onnx #raspberry_pi #risc_v #speech_to_text #text_to_speech #vits #windows

This tool supports various speech functions like speech recognition, text-to-speech, speaker identification, and more. It works on multiple platforms including Android, iOS, Windows, macOS, and Linux, and supports several programming languages such as C++, Python, JavaScript, and others. You can use it locally or through web assembly, making it versatile and convenient. This benefits you by allowing you to integrate advanced speech capabilities into your projects easily, regardless of the platform or programming language you use.

https://github.com/k2-fsa/sherpa-onnx

#java #anthropic #chatgpt #chroma #embeddings #gemini #gpt #huggingface #java #langchain #llama #milvus #ollama #onnx #openai #openai_api #pgvector #pinecone #vector_database #weaviate

LangChain4j helps you add powerful AI to your Java applications by making it easy to use Large Language Models (LLMs). It provides a simple way to switch between different LLMs and embedding stores without needing to learn each one's specific API. This means you can easily experiment with different models and tools, making your development process faster and more flexible. LangChain4j also offers many examples and tools to help you build complex AI applications quickly, such as chatbots and retrieval systems. This simplifies the integration of AI into your projects, allowing you to focus on creating better applications.

https://github.com/langchain4j/langchain4j

#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