#IOS#YOLOv5 🚀 是在 COCO 数据集上预训练的一系列对象检测架构和模型,代表 Ultralytics 对未来视觉 AI 方法的开源研究,结合了经过数千小时研究和开发的经验教训和最佳实践。
#计算机科学#Netron是一种用于神经网络、深度学习和机器学习模型的可视化工具
#计算机科学#A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computa...
翻译 - 快速,可扩展,高性能的“决策树加速梯度”库,用于对Python,R,Java,C ++进行排名,分类,回归和其他机器学习任务。支持在CPU和GPU上进行计算。
Run Stable Diffusion on Mac natively
#IOS#Largest list of models for Core ML (for iOS 11+)
翻译 - Core ML的最大型号列表(适用于iOS 11+)
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyT...
翻译 - MMdnn是一组工具,可帮助用户在不同的深度学习框架之间进行互操作。例如。模型转换和可视化。在Caffe,Keras,MXNet,Tensorflow,CNTK,PyTorch Onnx和CoreML之间转换模型。
#IOS#Native Mac APIs for Go. Previously known as MacDriver
翻译 - Go的本机Mac API
#计算机科学#Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.
翻译 - Core ML工具包含用于Core ML模型转换,编辑和验证的支持工具。
#人脸识别#由腾讯优图实验室开源的高性能、轻量级神经网络推理框架,同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。
A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), ...
翻译 - A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
#学习与技能提升#📚 Curated list of articles, tutorials and repos that may help you dig a little bit deeper into iOS [and Apple Platforms].
#IOS#Everything we actually know about the Apple Neural Engine (ANE)
Use AnimeGANv3 to make your own animation works, including turning photos or videos into anime.
Apple Silicon Guide. Learn all about the A17 Pro, A16 Bionic, R1, M1-series, M2-series, and M3-series chips. Along with all the Devices, Operating Systems, Tools, Gaming, and Software that Apple Sili...
#IOS#Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit project to use CoreML.