Top 22 efficientnet open source projects

⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

Implementation of EfficientNet model. Keras and TensorFlow Keras.

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.

Google Brain AutoML

Segmentation models with pretrained backbones. Keras and TensorFlow Keras.

More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet, efficientnet, hrnet, swin-transformer) and (cbam，dcn and so on), and tensorrt

Some parts of my code for the Computer Vision Kaggle Bengali AI Handwritten Grapheme Classification competition

Code for Video Deepfake Detection model from "Combining EfficientNet and Vision Transformers for Video Deepfake Detection" available on Arxiv and was submitted to ICIAP 2021.

A Gluon Implement of EfficientNet

Using deep learning models for image classification directly on the HoloLens 2.

detectron2 backbone: resnet18, efficientnet, hrnet, mobilenet v2, resnest, bifpn

A collection of deep learning models (PyTorch implemtation)

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.

EfficientNet, MobileNetV3, MobileNetV2, MixNet, etc in JAX w/ Flax Linen and Objax

PyTorch Implementation of the state-of-the-art model for object detection EfficientDet [pre-trained weights provided]

PyTorch implementation of EfficientNetV2 family

🍔🍟🍗 Food analysis baseline with Theseus. Integrate object detection, image classification and multi-class semantic segmentation. 🍞🍖🍕

A list of popular deep learning models related to classification, segmentation and detection problems

Concise, Modular, Human-friendly PyTorch implementation of MixNet with Pre-trained Weights.

Using efficientnet to provide embeddings for retrieval

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.