dynamic-training-with-apache-mxnet-on-awsDynamic training with Apache MXNet reduces cost and time for training deep neural networks by leveraging AWS cloud elasticity and scale. The system reduces training cost and time by dynamically updating the training cluster size during training, with minimal impact on model training accuracy.
Stars: ✭ 51 (-98.32%)
Deep-rl-mxnetMxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO
Stars: ✭ 26 (-99.14%)
Nest💡 A flexible tool for building and sharing deep learning modules.
Stars: ✭ 40 (-98.68%)
OpSummary.MXNetA tool to count operators and parameters of your MXNet-Gluon model.
Stars: ✭ 19 (-99.37%)
AIML-Human-Attributes-Detection-with-Facial-Feature-ExtractionThis is a Human Attributes Detection program with facial features extraction. It detects facial coordinates using FaceNet model and uses MXNet facial attribute extraction model for extracting 40 types of facial attributes. This solution also detects Emotion, Age and Gender along with facial attributes.
Stars: ✭ 48 (-98.41%)
onnx tensorrt projectSupport Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt
Stars: ✭ 145 (-95.21%)
iqiyi-vid-challengeCode for IQIYI-VID(IQIYI Video Person Identification) Challenge Implemented in Python and MXNet
Stars: ✭ 45 (-98.51%)
DLInfBenchCNN model inference benchmarks for some popular deep learning frameworks
Stars: ✭ 51 (-98.32%)
insightocrMXNet OCR implementation. Including text recognition and detection.
Stars: ✭ 100 (-96.7%)
robotFunctions and classes for gradient-based robot motion planning, written in Ivy.
Stars: ✭ 29 (-99.04%)
HandyRLHandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
Stars: ✭ 228 (-92.47%)
MXNet-YOLOmxnet implementation of yolo and darknet2mxnet converter
Stars: ✭ 17 (-99.44%)
mxnet-cpp-scratchSome deep learning models written with mxnet and C++11.
Stars: ✭ 14 (-99.54%)
pytorch-model-parallelA memory balanced and communication efficient FullyConnected layer with CrossEntropyLoss model parallel implementation in PyTorch
Stars: ✭ 74 (-97.56%)
capsnet.mxnetMXNet implementation of CapsNet
Stars: ✭ 30 (-99.01%)
mxnet-audioImplementation of music genre classification, audio-to-vec, song recommender, and music search in mxnet
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gluon2pytorchGluon to PyTorch deep neural network model converter
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mxtermexplore apache mxnet from the terminal / REPL
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mtomoMultiple types of NN model optimization environments. It is possible to directly access the host PC GUI and the camera to verify the operation. Intel iHD GPU (iGPU) support. NVIDIA GPU (dGPU) support.
Stars: ✭ 24 (-99.21%)
DockerKerasWe provide GPU-enabled docker images including Keras, TensorFlow, CNTK, MXNET and Theano.
Stars: ✭ 49 (-98.38%)
mlreefThe collaboration workspace for Machine Learning
Stars: ✭ 1,409 (-53.47%)
megaface-evaluationA Simple Tool to Evaluate Your Models on Megaface Benchmark Implemented in Python and Mxnet
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mxboxSimple, efficient and flexible vision toolbox for mxnet framework.
Stars: ✭ 31 (-98.98%)
MXNetDotNet.NET wrapper for Apache MXNet written in C#
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AAAI 2019 EXAMOfficial implementation of "Explicit Interaction Model towards Text Classification"
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mloperatorMachine Learning Operator & Controller for Kubernetes
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XLearning-GPUqihoo360 xlearning with GPU support; AI on Hadoop
Stars: ✭ 22 (-99.27%)
deepspeech.mxnetA MXNet implementation of Baidu's DeepSpeech architecture
Stars: ✭ 82 (-97.29%)
softmaxfocallossthe loss function in Aritcal ‘Focal Loss for Dense Object Detection‘’
Stars: ✭ 16 (-99.47%)
FacedetectionC++ project to implement MTCNN, a perfect face detect algorithm, on different DL frameworks. The most popular frameworks: caffe/mxnet/tensorflow, are all suppported now
Stars: ✭ 255 (-91.58%)
sfd.gluoncvReproduce SFD face detector using gluon-cv
Stars: ✭ 23 (-99.24%)
enhanced-ssh-mxnetThe MXNet Implementation of Enhanced SSH (ESSH) for Face Detection and Alignment
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torchxTorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
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Arch-Data-ScienceArchlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
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lipnetLipNet with gluon
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model-zoo-oldThe ONNX Model Zoo is a collection of pre-trained models for state of the art models in deep learning, available in the ONNX format
Stars: ✭ 38 (-98.75%)
DLARMDLARM: Dissertation for Computer Science Masters Degree at UFRGS
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HyperGBMA full pipeline AutoML tool for tabular data
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d2l-javaThe Java implementation of Dive into Deep Learning (D2L.ai)
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crnn.mxnetcrnn in mxnet.can train with chinese characters
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Deep Learning In ProductionIn this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Stars: ✭ 3,104 (+2.51%)
HetuA high-performance distributed deep learning system targeting large-scale and automated distributed training.
Stars: ✭ 78 (-97.42%)
onnx2tensorRttensorRt-inference darknet2onnx pytorch2onnx mxnet2onnx python version
Stars: ✭ 14 (-99.54%)
NonLocalandSEnetMXNet implementation of Non-Local and Squeeze-Excitation network
Stars: ✭ 24 (-99.21%)
PLSCPaddle Large Scale Classification Tools,supports ArcFace, CosFace, PartialFC, Data Parallel + Model Parallel. Model includes ResNet, ViT, DeiT, FaceViT.
Stars: ✭ 113 (-96.27%)