v1.2.2 (12/14/2023)

Bug Fixes

• Fix bug in cross entropy loss (#3457)
• Allow custom visualizer (#3455)
• test resize with pad_shape (#3421)
• add with-labels args to inferencer for visualization without labels (#3466)

New Contributors

• @okotaku made their first contribution in#3421

Contributors

v1.2.1 (10/17/2023)

Bug Fixes

• Add bpe_simple_vocab_16e6.txt.gz to release (#3386)
• Fix init api (#3388)

MMSegmentation v1.2.0 (10/12/2023)

From v1.1.0 to v1.2.0, we are delighted that MMSegmentation supports full-flowopen-vocabulary semantic segmentation andmonocular depth estimation tasks!

• Open-vocabulary semantic segmentation:SAN andCAT-Seg:

  • Side Adapter Network for Open-Vocabulary Semantic Segmentation
    
  • Cost Aggregation for Open-Vocabulary Semantic Segmentation
    

• Monocular depth estimation:VPD andAdaBins:

  • Visual Perception with Pre-trained Diffusion Models
    
  • AdaBins: Depth Estimation using Adaptive Bins:
    

Features

• Support Side Adapter Network (#3232)

Bug Fixes

• fix wrong variables passing forset_dataset_meta (#3348)

Documentation

• add documentation of Finetune ONNX Models (MMSegemetation) Inference for NVIDIA Jetson (#3372)

v1.1.2(09/20/2023)

Features

• Add semantic label to the segmentation visualization results (#3229)
• Support NYU depth estimation dataset (#3269)
• Support Kullback-Leibler divergence Loss (#3242)
• Support depth metrics (#3297)
• Support Remote sensing inferencer (#3131)
• Support VPD Depth Estimator ((#3321)(#3321))
• Support inference and visualization of VPD (#3331)
• Support using the pytorch-grad-cam tool to visualize Class Activation Maps (CAM) (#3324)

New projects

• Support PP-Mobilenet (#3239)
• Support CAT-Seg (CVPR'2023) (#3098)
• Support Adabins (#3257)
• Add pp_mobileseg onnx inference script (#3268)

Bug Fixes

• Fix module PascalContextDataset (#3235)
• Fix one hot encoding for dice loss (#3237)
• Fix confusion_matrix.py (#3291)
• Fix inferencer visualization (#3333)

Documentation

• Translate doc for docs/zh_cn/user_guides/5_deployment.md (#3281)

New Contributors

• @angiecao made their first contribution in#3235
• @yeedrag made their first contribution in#3237
• @Yang-Changhui made their first contribution in#3239
• @ooooo-create made their first contribution in#3261
• @Ben-Louis made their first contribution in#3269
• @crazysteeaam made their first contribution in#3284
• @zen0no made their first contribution in#3242
• @XiandongWang made their first contribution in#3291
• @ZhaoQiiii made their first contribution in#3332
• @zhen6618 made their first contribution in#3324

Contributors

v1.1.1(07/24/2023)

Features

• Add bdd100K datasets (#3158)
• Remove batch inference assertion (#3210)

Bug Fixes

• Fix train map path for coco-stuff164k.py (#3187)
• Fix mim search error (#3194)
• Fix SegTTAModel with no attribute '_gt_sem_seg' error (#3152)
• Fix Albumentations default key mapping mismatch (#3195)

New Contributors

• @OliverGrace made their first contribution in#3187
• @ZiAn-Su made their first contribution in#3152
• @CastleDream made their first contribution in#3158
• @coding-famer made their first contribution in#3174
• @Alias-z made their first contribution in#3195

Contributors

v1.1.0(07/04/2023)

Features

• Support albu transform (#2943)
• Support DDRNet (#2855)
• Add GDAL backend and Support LEVIR-CD Dataset (#2903)
• Support DSDL Dataset (#2925)
• huasdorff distance loss (#2820)

New Projects

• Support SAM inferencer (#2897)
• Added a supported for Visual Attention Network (VAN) (#2987)
• add GID dataset (#3038)
• add Medical semantic seg dataset: Bactteria (#2568)
• add Medical semantic seg dataset: Vampire (#2633)
• add Medical semantic seg dataset: Ravir (#2635)
• add Medical semantic seg dataset: Cranium (#2675)
• add Medical semantic seg dataset: bccs (#2861)
• add Medical semantic seg dataset: Gamma Task3 dataset (#2695)
• add Medical semantic seg dataset: consep (#2724)
• add Medical semantic seg dataset: breast_cancer_cell_seg dataset (#2726)
• add Medical semantic seg dataset: chest_image_pneum dataset (#2727)
• add Medical semantic seg dataset: conic2022 (#2725)
• add Medical semantic seg dataset: dr_hagis (#2729)
• add Medical semantic seg dataset: orvs (#2728)
• add Medical semantic seg dataset: ISIC-2016 Task1 (#2708)
• add Medical semantic seg dataset: ISIC-2017 Task1 (#2709)
• add Medical semantic seg dataset: Kvasir seg (#2677)
• add Medical semantic seg dataset: Kvasir seg aliyun (#2678)
• add Medical semantic seg dataset: Rite (#2680)
• add Medical semantic seg dataset: Fusc2021 (#2682)
• add Medical semantic seg dataset: 2pm vessel (#2685)
• add Medical semantic seg dataset: Pcam (#2684)
• add Medical semantic seg dataset: Pannuke (#2683)
• add Medical semantic seg dataset: Covid 19 ct cxr (#2688)
• add Medical semantic seg dataset: Crass (#2690)
• add Medical semantic seg dataset: Chest x ray images with pneumothorax masks (#2687)

Enhancement

• Robust mapping from image path to seg map path (#3091)
• Change assertion logic inference cfg.model.test_cfg (#3012)
• Refactor dice loss (#3002)
• Update Dockerfile libgl1-mesa-dev (#3095)
• Prevent passedann_file from silently failing to load (#2966)
• Update the translation of models documentation (#2833)
• Add docs contents at README.md (#3083)
• Enhance swin pretrained model loading (#3097)

Bug Fixes

• Handle case where device is neither CPU nor CUDA in HamHead (#2868)
• Fix bugs when out_channels==1 (#2911)
• Fix binary C=1 focal loss & dataset fileio (#2935)
• Fix isaid dataset pre-processing tool (#3010)
• Fix bug cannot use both '--tta' and '--out' while testing (#3067)
• Fix inferencer ut (#3117)
• Fix document (#2863,#2896,#2919,#2951,#2970,#2961,#3042, )
• Fix squeeze error when N=1 and C=1 (#2933)

New Contributors

• @liu-mengyang made their first contribution in#2896
• @likyoo made their first contribution in#2911
• @1qh made their first contribution in#2902
• @JoshuaChou2018 made their first contribution in#2951
• @jts250 made their first contribution in#2833
• @MGAMZ made their first contribution in#2970
• @tianbinli made their first contribution in#2568
• @Provable0816 made their first contribution in#2633
• @Zoulinx made their first contribution in#2903
• @wufan-tb made their first contribution in#2925
• @haruishi43 made their first contribution in#2966
• @Masaaki-75 made their first contribution in#2675
• @tang576225574 made their first contribution in#2987
• @Kedreamix made their first contribution in#3010
• @nightrain01 made their first contribution in#3067
• @shigengtian made their first contribution in#3095
• @SheffieldCao made their first contribution in#3097
• @wangruohui made their first contribution in#3091
• @LHamnett made their first contribution in#3012

Contributors

v1.0.0(04/06/2023)

Highlights

We are excited to announce the release of MMSegmentation v1.0.0 as a part of the OpenMMLab 2.0 project! MMSegmentation v1.0.0 introduces an updated framework structure for the core package and a new section called "Projects". This section showcases a range of engaging and versatile applications built upon the MMSegmentation foundation.

In this latest release, we have significantly refactored the core package's code to make it clearer, more comprehensible, and disentangled. This has resulted in improved performance for several existing algorithms, ensuring that they now outperform their previous versions. Additionally, we have incorporated some cutting-edge algorithms, such as PIDNet and SegNeXt, to further enhance the capabilities of MMSegmentation and provide users with a more comprehensive and powerful toolkit.
The new "Projects" section serves as an essential addition to MMSegmentation, created to foster innovation and collaboration among users.

Exciting Features

Inferencer

In this release, we introduce the MMSegInferencer, a versatile API for inference that accommodates multiple input types. The API enables users to easily specify and customize semantic segmentation models, streamlining the process of performing semantic segmentation with MMSegmentation.

Usage:

python demo/image_demo_with_inferencer.py${IMAGE}${MODEL} --show --device${DEVICE}

Optimizations

In addition to new features, MMSegmentation v1.0.0 delivers key optimizations for an enhanced user experience.

PyTorch 2.0 Compatibility

MMSegmentation v1.0.0 is now compatible with PyTorch 2.0, ensuring that users can leverage the latest features and performance improvements offered by the PyTorch 2.0 framework when using MMSegmentation. With the integration of inductor, users can expect faster model speeds. The table below shows several example models:

New Features

New features from v1.0.0rc6 to v1.0.0 include:

• Add Mapillary Vistas Datasets support to MMSegmentation Core Package (#2576)
• Support PIDNet (#2609)
• Support SegNeXt (#2654)
• Support calculating FLOPs of segmentors (#2706)
• Support multi-band image for Mosaic (#2748)
• Support dump segment prediction (#2712)

Bug fix

• Fix format_result and fix prefix param in cityscape metric, and rename CitysMetric to CityscapesMetric (#2660)
• Support input gt seg map is not 2D (#2739)
• Fix accepting an unexpected argumentlocal-rank in PyTorch 2.0 (#2812)

Documentation

• Add Chinese version of various documentation (#2673,#2702,#2703,#2701,#2722,#2733,#2769,#2790,#2798)
• Update and refine various English documentation (#2715,#2755,#2745,#2797,#2799,#2821,#2827,#2831)
• Add deeplabv3 model structure documentation (#2426)
• Add custom metrics documentation (#2799)
• Add faq in dev-1.x branch (#2765)

New Contributors

• @liuruiqiang made their first contribution in#2554
• @wangjiangben-hw made their first contribution in#2569
• @jinxianwei made their first contribution in#2557
• @KKIEEK made their first contribution in#2747
• @Renzhihan made their first contribution in#2765

Contributors

v1.0.0rc6(03/03/2023)

Highlights

• Support MMSegInferencer (#2413,#2658), which is a easy-to-use hight level api for model inference.

>>>frommmseg.apisimportMMSegInferencer>>># Initialize an inference>>>inferencer=MMSegInferencer(model='deeplabv3plus_r18-d8_4xb2-80k_cityscapes-512x1024')>>># Inference>>>inferencer('demo/demo.png',show=True)>>># Get all models in MMSegmentation>>>models=MMSegInferencer.list_models('mmseg')

• Support REFUGE dataset (#2554)

Features

• Add browse_dataset.py script inmmsegmentation/tools/ (#2649)
• Support auto import modules from registry (#2481)
• Replace numpy ascontiguousarray with torch contiguous to speed-up (#2604)

Bug fix

• Rename and Fix bug of projects HieraSeg (#2565)
• Add out_channels inCascadeEncoderDecoder and update OCRNet and MobileNet v2 results (#2656)

Documentation

• Add dataflow documentation of Chinese version (#2652)
• Add customized runtime documentation of English version (#2533)
• Add documentation for visualizing feature map using wandb backend (#2557)
• Add documentation for benchmark results on NPU (HUAWEI Ascend) (#2569,#2596,#2610)
• Fix API name error in the migration doc (#2601)
• Refine projects documentation (#2586)
• Refine MMSegmentation documentation (#2668,#2659)

New Contributors

• @zccjjj made their first contribution in#2548
• @liuruiqiang made their first contribution in#2554
• @wangjiangben-hw made their first contribution in#2569
• @jinxianwei made their first contribution in#2557

Contributors

v1.0.0rc5(02/01/2023)

Bug fix

• Fix MaskFormer and Mask2Former when install mmdet from source (#2532)
• Support new fileio interface inMMCV>=2.0.0rc4 (#2543)
• Fix ERFNet URL in dev-1.x branch (#2537)
• Fix misleadingList[Tensor] types (#2546)
• Rename typing.py to typing_utils.py (#2548)

New Contributors

• @zccjjj made their first contribution in#2548

Contributors

v1.0.0rc4(30/01/2023)

Highlights

• Support ISNet (ICCV'2021) in projects (#2400)
• Support HSSN (CVPR'2022) in projects (#2444)

Features

• Add Gaussian Noise and Blur for biomedical data (#2373)
• Add BioMedicalRandomGamma (#2406)
• Add BioMedical3DPad (#2383)
• Add BioMedical3DRandomFlip (#2404)
• Addgt_edge_map field to SegDataSample (#2466)
• Support synapse dataset (#2432,#2465)
• Support Mapillary Vistas Dataset in projects (#2484)
• Switch order ofreduce_zero_label and applyinglabel_map (#2517)

Documentation

• Add ZN Customized_runtime Doc (#2502)
• Add EN datasets.md (#2464)
• Fix minor typo in migrationpackage.md (#2518)

Bug fix

• Fix incorrectimg_shape value assignment in RandomCrop (#2469)
• Fix inference api and support setting palette to SegLocalVisualizer (#2475)
• Unfinished label conversion from-1 to255 (#2516)

New Contributors

• @blueyo0 made their first contribution in#2373
• @Fivethousand5k made their first contribution in#2406
• @suyanzhou626 made their first contribution in#2383
• @unrealMJ made their first contribution in#2400
• @Dominic23331 made their first contribution in#2432
• @AI-Tianlong made their first contribution in#2444
• @morkovka1337 made their first contribution in#2492
• @Leeinsn made their first contribution in#2404
• @siddancha made their first contribution in#2516

Contributors