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).

A simple scheduler for OCaml 5

ICNet implemented by pytorch, for real-time semantic segmentation on high-resolution images, mIOU=71.0 on cityscapes, single inference time is 19ms, FPS is 52.6.

Boost segmentation model mIoU/Dice instantly WITHOUT retraining. A plug-and-play, training-free optimization module. Published in NeurIPS & JMLR. Compatible with SAM, DeepLab, SegFormer, and more. 🧩

FCN for Semantic Image Segmentation achieving 68.5 mIoU on PASCAL VOC

The 2nd solution (68.1 mIoU) for 1st Urban3D challenge.

No description available

Real-time semantic segmentation is widely used in the field of autonomous driving and robotics. Most previous networks achieved great accuracy based on a complicated model involving mass computing. The existing lightweight networks generally reduce the parameter sizes by sacrificing the segmentation accuracy. It is critical to balance the parameters and accuracy for real-time semantic segmentation tasks. In this paper, we introduce a Lightweight-Multiscale-Feature-Fusion Network (LMFFNet) mainly composed of three types of components: Split-Extract-Merge Bottleneck (SEM-B) block, Features Fusion Module (FFM), and Multiscale Attention Decoder (MAD). The SEM-B block extracts sufficient features with fewer parameters. FFMs fuse multiscale semantic features to effectively improve the segmentation accuracy. The MAD well recovers the details of the input images through the attention mechanism. Two networks combined with different components are proposed based on the LMFFNet model. Without pretraining, the smaller network of LMFFNet-S achieves 72.7% mIoU on Cityscapes test set at the 512×1024 resolution with only 1.1 M parameters at a reference speed of 98.9 fps running on a GTX1080Ti GPU while the larger version of LMFFNet-L achieves 74.7% mIoU with 1.4 M parameters at 89.6 fps. Besides, 67.7% mIoU at 208.9 fps and 70.3% mIoU at 72.4 fps are respectively achieved for 360 × 480 and 720 × 960 resolutions on CamVid test set using LMFFNet-S while LMFFNet--L achieves 68.1% mIoU at 182.9 fps and 71.0% mIoU at 66.5 fps, correspondingly. The proposed LMFFNets make an adequate trade-off between accuracy and parameter size for real-time inference for semantic segmentation tasks.

No description available

Aerial Drone Image Semantic Segmentation using U-Net with MobileNetV2 as the backbone architecture in Pytorch

自然环境以及白背景下单片西瓜叶片分割模型以及利用MIOU（平均交并比）算法进行评估、分割结果展示

The Purr App

calculating the mIOU of each class with given labels and model's result

In this research, a novel approach has been presented for multi-label semantic segmentation of the martian terrain for navigation using variants of a transformer model - SegFormer, which has resulted in a commendable accuracy of 90.86% and mIoU of 83.55% on the AI4Mars dataset

No description available

API wrapper

gif jpg hd dice miou segmentation

Open solution for 2018 Data ScienceBowl competition from kaggle. 28th place, 0.569 mIoU score.

This repository implements Defect Detection and Instance Segmentation on the CSDD (Collective Surface Defect Datasets) using Ultralytics YOLOv8.It covers three specific defect types: Scratch, Spot, and Rust. The project includes scripts for data preparation, model training, performance evaluation (including pixel-level mIoU), and visualization.

A streaming library for Miou

No description available

Multidimensional Imaging of Ultrafast Laser Pulses

this is a tensorflow repo for denseaspp net,and achieve 79.5% miou in Cityscapes val

Portrait segmentation evaluation script that computes mIoU, Boundary F1, and Boundary IoU from binary mask predictions to measure both region and boundary accuracy.

Designed 5 semantic segmentation models (Attention U-Net, Residual U-Net, DeepLabV3+) for adverse weather scene segmentation; applied multispectral fusion (RGB + NIR + Thermal) reducing misclassifications by 20%; introduced Safe-mIoU metric with tree-distance safety penalties, uncovering 15% more critical risks than standard mIoU.

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Big Collab with madame MAKARISON MAC MIOU FO, Céline, Laura and Layssa !!

Miou !:3

Dofus Bot MITM in C# under development

A matrix bot to query a terraforming mars server