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[Feature] Support Delving into High-Quality Synthetic Face Occlusion Segmentation Datasets #2194

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merged 17 commits into from
Nov 11, 2022
Merged

[Feature] Support Delving into High-Quality Synthetic Face Occlusion Segmentation Datasets #2194

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e9e196f
add custom dataset
jinwonkim93 Sep 20, 2022
d5e79fa
Merge branch 'open-mmlab:master' into custom/face_occlusion
jinwonkim93 Oct 11, 2022
23c9fd7
add config file for occlusion face
Oct 16, 2022
f4022fb
Merge pull request #1 from jinwonkim93/face_occlusion
jinwonkim93 Oct 16, 2022
e1cc800
add face occlusion dataset
Oct 16, 2022
33156d0
Merge branch 'custom/face_occlusion' of https://github.com/jinwonkim9…
Oct 16, 2022
1ca1780
fix format
Oct 17, 2022
69b49cd
update prepare.md
Oct 17, 2022
e4a9dd7
formatting
jinwonkim93 Oct 17, 2022
1fc898c
formatting
jinwonkim93 Oct 17, 2022
f537397
Merge branch 'open-mmlab:master' into custom/face_occlusion
jinwonkim93 Oct 24, 2022
c222684
Merge branch 'open-mmlab:master' into custom/face_occlusion
jinwonkim93 Oct 26, 2022
280b175
Merge branch 'open-mmlab:master' into custom/face_occlusion
jinwonkim93 Nov 1, 2022
2aaa757
fix typo error for doc
jinwonkim93 Nov 1, 2022
dd59be3
update downloading process
jinwonkim93 Nov 2, 2022
62bcc1a
Merge branch 'open-mmlab:master' into custom/face_occlusion
jinwonkim93 Nov 8, 2022
70b2853
Update dataset_prepare.md
jinwonkim93 Nov 10, 2022
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update downloading process
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@jinwonkim93
jinwonkim93 committed Nov 2, 2022
commit dd59be35833accfc0ae1d8bed872475ae733e1ed
25 changes: 20 additions & 5 deletions docs/en/dataset_prepare.md
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Expand Up @@ -400,22 +400,37 @@ The dataset is generated by two techniques, Naturalistic occlusion generation, R

## Dataset Preparation

Please download the masks from this [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing) and the images from [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ), [11k Hands](https://sites.google.com/view/11khands) and [DTD](https://www.robots.ox.ac.uk/~vgg/data/dtd/).
step 1

The extracted and upsampled COCO objects images and masks can be found in this [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing).

Please extract CelebAMask-HQ and 11k Hands images based on the splits found in [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing).
Create a folder for data generation materials on mmsegmentation folder.

```shell
mkdir data_materials
```

step 2

Please download the masks (11k-hands_mask.7z,CelebAMask-HQ-masks_corrected.7z) from this [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing)

Please download the images from [CelebAMask-HQ](https://github.com/switchablenorms/CelebAMask-HQ), [11k Hands.zip](https://sites.google.com/view/11khands) and [dtd-r1.0.1.tar.gz](https://www.robots.ox.ac.uk/~vgg/data/dtd/).

step 3

Download a upsampled COCO objects images and masks (coco_object.7z). files can be found in this [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing).

Download CelebAMask-HQ and 11k Hands images split txt files. (11k_hands_sample.txt, CelebAMask-HQ-WO-train.txt) found in [drive](https://drive.google.com/drive/folders/15nZETWlGMdcKY6aHbchRsWkUI42KTNs5?usp=sharing).

download file to ./data_materials

```none
CelebAMask-HQ.zip
CelebAMask-HQ-masks_corrected.7z
CelebAMask-HQ-WO-train.txt
RealOcc.7z
RealOcc-Wild.7z
11k-hands_mask.7z
11k-hands_image.7z
11k Hands.zip
11k_hands_sample.txt
coco_object.7z
dtd-r1.0.1.tar.gz
```
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