| ## Prepare datasets | |
| It is recommended to symlink the dataset root to `$MMSEGMENTATION/data`. | |
| If your folder structure is different, you may need to change the corresponding paths in config files. | |
| ```none | |
| mmsegmentation | |
| ├── mmseg | |
| ├── tools | |
| ├── configs | |
| ├── data | |
| │ ├── cityscapes | |
| │ │ ├── leftImg8bit | |
| │ │ │ ├── train | |
| │ │ │ ├── val | |
| │ │ ├── gtFine | |
| │ │ │ ├── train | |
| │ │ │ ├── val | |
| │ ├── VOCdevkit | |
| │ │ ├── VOC2012 | |
| │ │ │ ├── JPEGImages | |
| │ │ │ ├── SegmentationClass | |
| │ │ │ ├── ImageSets | |
| │ │ │ │ ├── Segmentation | |
| │ │ ├── VOC2010 | |
| │ │ │ ├── JPEGImages | |
| │ │ │ ├── SegmentationClassContext | |
| │ │ │ ├── ImageSets | |
| │ │ │ │ ├── SegmentationContext | |
| │ │ │ │ │ ├── train.txt | |
| │ │ │ │ │ ├── val.txt | |
| │ │ │ ├── trainval_merged.json | |
| │ │ ├── VOCaug | |
| │ │ │ ├── dataset | |
| │ │ │ │ ├── cls | |
| │ ├── ade | |
| │ │ ├── ADEChallengeData2016 | |
| │ │ │ ├── annotations | |
| │ │ │ │ ├── training | |
| │ │ │ │ ├── validation | |
| │ │ │ ├── images | |
| │ │ │ │ ├── training | |
| │ │ │ │ ├── validation | |
| │ ├── CHASE_DB1 | |
| │ │ ├── images | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ │ ├── annotations | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ ├── DRIVE | |
| │ │ ├── images | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ │ ├── annotations | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ ├── HRF | |
| │ │ ├── images | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ │ ├── annotations | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ ├── STARE | |
| │ │ ├── images | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| │ │ ├── annotations | |
| │ │ │ ├── training | |
| │ │ │ ├── validation | |
| ``` | |
| ### Cityscapes | |
| The data could be found [here](https://www.cityscapes-dataset.com/downloads/) after registration. | |
| By convention, `**labelTrainIds.png` are used for cityscapes training. | |
| We provided a [scripts](https://github.com/open-mmlab/mmsegmentation/blob/master/tools/convert_datasets/cityscapes.py) based on [cityscapesscripts](https://github.com/mcordts/cityscapesScripts) | |
| to generate `**labelTrainIds.png`. | |
| ```shell | |
| # --nproc means 8 process for conversion, which could be omitted as well. | |
| python tools/convert_datasets/cityscapes.py data/cityscapes --nproc 8 | |
| ``` | |
| ### Pascal VOC | |
| Pascal VOC 2012 could be downloaded from [here](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar). | |
| Beside, most recent works on Pascal VOC dataset usually exploit extra augmentation data, which could be found [here](http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/semantic_contours/benchmark.tgz). | |
| If you would like to use augmented VOC dataset, please run following command to convert augmentation annotations into proper format. | |
| ```shell | |
| # --nproc means 8 process for conversion, which could be omitted as well. | |
| python tools/convert_datasets/voc_aug.py data/VOCdevkit data/VOCdevkit/VOCaug --nproc 8 | |
| ``` | |
| Please refer to [concat dataset](https://github.com/open-mmlab/mmsegmentation/blob/master/docs/tutorials/new_dataset.md#concatenate-dataset) for details about how to concatenate them and train them together. | |
| ### ADE20K | |
| The training and validation set of ADE20K could be download from this [link](http://data.csail.mit.edu/places/ADEchallenge/ADEChallengeData2016.zip). | |
| We may also download test set from [here](http://data.csail.mit.edu/places/ADEchallenge/release_test.zip). | |
| ### Pascal Context | |
| The training and validation set of Pascal Context could be download from [here](http://host.robots.ox.ac.uk/pascal/VOC/voc2010/VOCtrainval_03-May-2010.tar). You may also download test set from [here](http://host.robots.ox.ac.uk:8080/eval/downloads/VOC2010test.tar) after registration. | |
| To split the training and validation set from original dataset, you may download trainval_merged.json from [here](https://codalabuser.blob.core.windows.net/public/trainval_merged.json). | |
| If you would like to use Pascal Context dataset, please install [Detail](https://github.com/zhanghang1989/detail-api) and then run the following command to convert annotations into proper format. | |
| ```shell | |
| python tools/convert_datasets/pascal_context.py data/VOCdevkit data/VOCdevkit/VOC2010/trainval_merged.json | |
| ``` | |
| ### CHASE DB1 | |
| The training and validation set of CHASE DB1 could be download from [here](https://staffnet.kingston.ac.uk/~ku15565/CHASE_DB1/assets/CHASEDB1.zip). | |
| To convert CHASE DB1 dataset to MMSegmentation format, you should run the following command: | |
| ```shell | |
| python tools/convert_datasets/chase_db1.py /path/to/CHASEDB1.zip | |
| ``` | |
| The script will make directory structure automatically. | |
| ### DRIVE | |
| The training and validation set of DRIVE could be download from [here](https://drive.grand-challenge.org/). Before that, you should register an account. Currently '1st_manual' is not provided officially. | |
| To convert DRIVE dataset to MMSegmentation format, you should run the following command: | |
| ```shell | |
| python tools/convert_datasets/drive.py /path/to/training.zip /path/to/test.zip | |
| ``` | |
| The script will make directory structure automatically. | |
| ### HRF | |
| First, download [healthy.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/healthy.zip), [glaucoma.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/glaucoma.zip), [diabetic_retinopathy.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/diabetic_retinopathy.zip), [healthy_manualsegm.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/healthy_manualsegm.zip), [glaucoma_manualsegm.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/glaucoma_manualsegm.zip) and [diabetic_retinopathy_manualsegm.zip](https://www5.cs.fau.de/fileadmin/research/datasets/fundus-images/diabetic_retinopathy_manualsegm.zip). | |
| To convert HRF dataset to MMSegmentation format, you should run the following command: | |
| ```shell | |
| python tools/convert_datasets/hrf.py /path/to/healthy.zip /path/to/healthy_manualsegm.zip /path/to/glaucoma.zip /path/to/glaucoma_manualsegm.zip /path/to/diabetic_retinopathy.zip /path/to/diabetic_retinopathy_manualsegm.zip | |
| ``` | |
| The script will make directory structure automatically. | |
| ### STARE | |
| First, download [stare-images.tar](http://cecas.clemson.edu/~ahoover/stare/probing/stare-images.tar), [labels-ah.tar](http://cecas.clemson.edu/~ahoover/stare/probing/labels-ah.tar) and [labels-vk.tar](http://cecas.clemson.edu/~ahoover/stare/probing/labels-vk.tar). | |
| To convert STARE dataset to MMSegmentation format, you should run the following command: | |
| ```shell | |
| python tools/convert_datasets/stare.py /path/to/stare-images.tar /path/to/labels-ah.tar /path/to/labels-vk.tar | |
| ``` | |
| The script will make directory structure automatically. | |