This is a project aiming at training an AI model for semantic segmentation purpose. The specific target is for extracting road segmentation from an image or a video on edge devices.

bisenetv2-tensorflow

Unofficial tensorflow implementation of real-time scene image segmentation model "BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation"

can301

clip-mesh-smplx

CLIP + Mesh + SMPL-X

codeforces-go

算法竞赛模板库 by 灵茶山艾府 💭💡🎈

cpt204back

XjtluerBonding

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

deep_lip_reading

Code and models for evaluating a state-of-the-art lip reading network

deeplab-v3-plus-cityscapes

mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).

deeplabv3.pytorch

PyTorch implementation of DeepLabv3

deeplabv3city

PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.

deeplabv3plus

deeplabv3plus2018:Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation

deeplabv3plus-pytorch

DeepLabv3 and DeepLabv3+ with pretrained weights for Pascal VOC & Cityscapes

deeplabv3plus-pytorch-1

Here is a pytorch implementation of deeplabv3+ supporting ResNet(79.155%) and Xception(79.945%). Multi-scale & flip test and COCO dataset interface has been finished.