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Environment

  • Version
    • torch 1.6.0, cu101

Build Detectron2 Using Docker

# build image
docker build --build-arg USER_ID=$UID -t fashion ./docker

# build container from the image
docker run --gpus all -it -p 8282:8282 -p 6006:6006 --shm-size=8gb --env="DISPLAY" -v ~/Documents/dataset/fashion/:/home/appuser/fashion_repo/dataset --name=fashion fashion:latest
  • ~/Documents/dataset/fashion/: your data path in host
  • /home/appuser/fashion_repo/dataset: your data path in docker
# Access to container
docker exec -it fashion bash

Dataset

Segmentation Task

  • Cascade mask rcnn

sh script/run_seg_deepfahsion_cascade.sh 
sh script/run_seg_deepfahsion_cascade.sh
  • Output

Performance for Deepfashion-v2

  • Distribution of instances among all 13 categories for training :
category #instances category #instances category #instances
short sleev.. 71645 long sleeve.. 36064 short sleev.. 543
long sleeve.. 13457 vest 16095 sling 1985
shorts 36616 trousers 55387 skirt 30835
short sleev.. 17211 long sleeve.. 7907 vest dress 17949
sling dress 6492
total 312186
  • Evaluation results for bbox:
AP AP50 AP75 APs APm APl
55.866 67.401 62.356 0.228 31.682 57.903
  • Per-category bbox AP:
category AP category AP category AP
short sleeve top 84.388 long sleeve top 64.570 short sleeve outwear 7.145
long sleeve outwear 22.648 vest 64.892 sling 41.982
shorts 68.366 trousers 67.217 skirt 72.668
short sleeve dress 67.721 long sleeve dress 45.859 vest dress 66.793
sling dress 52.014
  • Evaluation results for segm:
AP AP50 AP75 APs APm APl
52.244 66.834 61.169 0.000 22.458 54.445
  • Per-category segm AP:
category AP category AP category AP
short sleeve top 79.983 long sleeve top 58.647 short sleeve outwear 5.507
long sleeve outwear 18.926 vest 61.006 sling 36.943
shorts 64.316 trousers 59.996 skirt 71.021
short sleeve dress 64.007 long sleeve dress 42.682 vest dress 62.124
sling dress 54.019

Performance for Kfashion

  • Distribution of instances among all 21 categories for training :
category #instances category #instances category #instances
cardigan 133 knitwear 662 dress 2042
leggings 43 vest 99 bratop 14
blouse 1281 shirts 344 skirt 957
jacket 267 jumper 149 jumpsuit 81
jogger pants 68 zipup 28 jean 698
coat 234 top 453 t-shirts 1514
padded jacket 66 pants 1592 hoody 156
total 10881
  • Evaluation results for bbox:
AP AP50 AP75 APs APm APl
59.341 72.345 66.059 50.000 56.079 59.267
  • Per-category bbox AP:
category AP category AP category AP
cardigan 51.548 knitwear 69.198 dress 83.673
leggings 41.134 vest 56.446 bratop 48.868
blouse 68.417 shirts 45.178 skirt 72.048
jacket 58.181 jumper 54.128 jumpsuit 56.432
jogger pants 44.613 zipup 34.958 jean 70.600
coat 78.221 top 32.488 t-shirts 65.541
padded jacket 83.620 pants 64.075 hoody 66.799
  • Evaluation results for segm:
AP AP50 AP75 APs APm APl
51.726 71.804 58.591 30.000 44.805 51.682
  • Per-category segm AP:
category AP category AP category AP
cardigan 37.292 knitwear 65.304 dress 77.239
leggings 26.938 vest 42.535 bratop 46.223
blouse 61.723 shirts 41.485 skirt 71.209
jacket 45.287 jumper 44.823 jumpsuit 47.319
jogger pants 40.278 zipup 29.540 jean 61.408
coat 69.032 top 29.066 t-shirts 58.393
padded jacket 74.742 pants 55.881 hoody 60.534

Recommendation Task

sh script/run_cgd_extraction.sh

  • Get items by using cosine similarities, and evaluation

    • CGD evaluation
    k Recall@k Hit@k MRR@k
    1 12.84 57.76 57.76
    2 18.33 63.95 686
    5 27.93 79.9 62.82
    10 34.77 77.23 63.55
    20 41.61 81.57 63.85
    • CGD + whitened PCA evaluation
    k Recall@k Hit@k MRR@k
    1 13.64 62.22 62.22
    2 19.92 68.02 65.12
    5 382 74.16 66.84
    10 38.56 81.02 67.67
    20 44.60 84.56 67.92

Extract Segmented Image for DB

sh script/run_seg_image.sh
  • Output