BoostCamp AI Tech P Stage stage3 Image Segmentation
- Segmentation
* JooYoung_dev
* HyeongMing_dev
* JunCheol_dev
* Kimin_dev
* MinJung_dev
* NuRee_dev - Detection
* JooYoung_dev
* HyeongMing_dev
* JunCheol_dev
* Kimin_dev
* MinJung_dev
* NuRee_dev
You can see this branch at main too.
$> tree -d
.
├── segmentaions
| ├── config
| ├── data
| ├── losses
| ├── models
| ├── scheduler
| ├── utils
│ └── ...
└── detection
└── ...
- config
* efficient b2/b6 + unet++
* efficient b4/b6 + deepLabV3+
* effunext
* resnext101 + upernet
* resnext50 + deepLabV3+
* unext - losses
* dice_ce_loss
* soft_ce_loss - scheduler * customcosine
$> tree -d
.
├── Segmentaion
│ └── ...
└── detection
└── ...
- model: resnext50_32x4d + DeepLabV3+
However, because used smp, you can use others in smp
$> tree -d
.
├── segmentaion
| ├── ppt_paper
│ └── ...
└── detection
└── ...
- ppt_paper
* segmentation_survey_2020.pdf
* Rethinking Pre-training and Self-training.pptx
* Imgage Segmentation.pptx
* EDA.pptx - model: emanet
$> tree -d
.
├── segmentaions
│ └── ...
└── detection
└── ...
- TTA_CRF
- psheudo_train
$> tree -d
.
├── seg
| ├── Tools
| ├── dataset
| ├── lib
| ├── preprocess
│ └── ...
└── detection
└── ...
- lib
* asgnet
* hrdnet
$> tree -d
.
├── segmentation
│ └── ...
└── detection
└── ...
- augmentaion test
- Resnext50 + DeepLabV3+
$> tree -d
.
├── segmentaions
│ └── ...
└── detection
├── UniverseNet-master
└── ...
mmdet
- universNet
$> tree -d
.
├── segmentaion
│ └── ...
└── ObjectDetection
├── Swin-Transformer-Object-Detection
└── ...
mmdet
- detectoRS + ResNeXt101
$> tree -d
.
├── segmentaion
│ └── ...
└── ObjectDetection
├── Swin-Transformer-Object-Detection
└── ...
mmdet
- Swin-S
$> tree -d
.
├── segmentaions
│ └── ...
└── detection
├── efficientdet-naive-pytorch
├── faster_rcnn-naive-pytorch
└── vfnetx-mmdet
naive model
- efficientdet
- faster_rcnn
mmdet
- vfnetx
$> tree -d
.
├── seg
│ └── ...
└── detection
├── Swin-Transformer-Object-Detection-master
├── mmdet
└── augmentaion
mmdet
- Swin-T
- efficienet b3 - nas-fpn - cascade rcnn
$> tree -d
.
├── segmentation
│ └── ...
└── detection
├── Swin-Transformer-Object-Detection-master
└── ...
mmdet
- Swin-T