70 Open Source Efficientnet Software Projects
Free and open source efficientnet code projects including engines, APIs, generators, and tools.
Pytorch Image Models 16145 ⭐
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
Yet Another Efficientdet Pytorch 4965 ⭐
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
Segmentation_models 3653 ⭐
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
Toandaominh1997 Efficientdet.pytorch 1420 ⭐
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
Gen Efficientnet Pytorch 1425 ⭐
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
Efficientdet Pytorch 1284 ⭐
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
Signatrix Efficientdet 583 ⭐
(Pretrained weights provided) EfficientDet: Scalable and Efficient Object Detection implementation by Signatrix GmbH
Basic_cnns_tensorflow2 463 ⭐
A tensorflow2 implementation of some basic CNNs(MobileNetV1/V2/V3, EfficientNet, ResNeXt, InceptionV4, InceptionResNetV1/V2, SENet, SqueezeNet, DenseNet, ShuffleNetV2, ResNet).
Efficientnets Pytorch 291 ⭐
A PyTorch implementation of " EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks."
Awesome Computer Vision Models 360 ⭐
A list of popular deep learning models related to classification, segmentation and detection problems
Lightnetplusplus 226 ⭐
LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation
Fastseg 261 ⭐
📸 PyTorch implementation of MobileNetV3 for real-time semantic segmentation, with pretrained weights & state-of-the-art performance
Pytorch Imagenet Cifar Coco Voc Training 222 ⭐
Training examples and results for ImageNet(ILSVRC2012)/COCO2017/VOC2007+VOC2012 datasets.Include ResNet/DarkNet/RegNet/RetinaNet/FCOS/CenterNet/YOLO series.
Efficientnet Pytorch 94 ⭐
A PyTorch implementation of "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks".
Detectron2_backbone 155 ⭐
detectron2 backbone: resnet18, efficientnet, hrnet, mobilenet v2, resnest, bifpn
Efficientnet.pytorch 27 ⭐
Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights.
Efficientnet Retinanet 35 ⭐
Pytorch implementation of RetinaNet using EfficientNets as feature extractor or backbone network.
Covid 19 Detector 16 ⭐
Repository containing scripts to train and test a neural network whose goal is to detect presence of COVID-19
Sevakon Efficientdet 20 ⭐
PyTorch Implementation of the state-of-the-art model for object detection EfficientDet [pre-trained weights provided]
Ensemble Of Multi Scale Cnn For Dermatoscopy Classification 22 ⭐
Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.
Faster_rcnn_sku110 30 ⭐
VoVNet, MobileNet, ShuffleNet, HarDNet, GhostNet, EfficientNet backbone networks and SKU-110K dataset for detectron2
Mixnet Pytorch 15 ⭐
Concise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights.
Nbdt Pytorch Image Models 12 ⭐
Neural-Backed Decision Tree sample integration with pytorch-image-models
Mixmatch Transferlearning 10 ⭐
Combines the SSL Method MixMatch with a pre-trained model (EfficientNet) on a chest x-ray dataset.
Nanodet 4017 ⭐
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Flexible Yolov5 267 ⭐
More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer) and (cbam，dcn and so on), and tensorrt
Efficientnet Jax 84 ⭐
EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax
Divide And Co Training 80 ⭐
[Paper 2020] Towards Better Accuracy-efficiency Trade-offs: Divide and Co-training. Plus, an image classification toolbox includes ResNet, Wide-ResNet, ResNeXt, ResNeSt, ResNeXSt, SENet, Shake-Shake, DenseNet, PyramidNet, and EfficientNet.
Hololens2 Machine Learning 36 ⭐
Using deep learning models for image classification directly on the HoloLens 2.
Kagglebengaliaihandwrittengraphemeclassification 25 ⭐
Some parts of my code for the Computer Vision Kaggle Bengali AI Handwritten Grapheme Classification competition
Masked_face_recognition 40 ⭐
2020/2021 HKUST CSE FYP Masked Facial Recognition, developer: Sam Yuen, Alex Xie, Tony Cheng
Research Paper Summary 29 ⭐
Summary & Implementation of Deep Learning research paper in Tensorflow/Pytorch.
Jittor Image Models 28 ⭐
Jittor Image Models is a library for pulling together a wide variety of SOTA deep learning models in the Jittor framework.
Keywordsspotting Efficientnet A0 16 ⭐
EfficientNet-Absolute Zero for Continuous Speech Keyword Spotting
Real Time Super Resolution 34 ⭐
🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
Pytorch Fpn 15 ⭐
PyTorch implementation of some FPN-based semantic segmentation architectures: vanilla FPN, Panoptic FPN, PANet FPN; with ResNet and EfficientNet backbones.
Geometry Preserving De 12 ⭐
Towards General Purpose, Geometry Preserving Single-View Depth Estimation https://arxiv.org/abs/2009.12419
Surgeon Assist Net 11 ⭐
Towards context-aware head-mounted display-based augmented reality for surgical guidance.
Efficientnet Bifpn Bilstm Behavior Recognition 10 ⭐
An efficient and multi-scale feature fusion behavior recognition algorithm
Food Detection Yolov5 16 ⭐
Food detection using YOLOv5 on images, videos, youtube urls. Also analyze nutrients of meal in the image. Support on web and android app.
Efficientunetplusplus 12 ⭐
Decoder architecture based on the UNet++. Combining residual bottlenecks with depthwise convolutions and attention mechanisms, it outperforms the UNet++ in a coronary artery segmentation task, while being significantly more computationally efficient.