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  1. 00280/img-mean-std-00280002.npy +3 -0
  2. 00280/img-mean-std-00280005.npy +3 -0
  3. 00280/img-mean-std-00280028.npy +3 -0
  4. 00280/img-mean-std-00280030.npy +3 -0
  5. 00280/img-mean-std-00280037.npy +3 -0
  6. 00280/img-mean-std-00280039.npy +3 -0
  7. 00280/img-mean-std-00280041.npy +3 -0
  8. 00280/img-mean-std-00280042.npy +3 -0
  9. 00280/img-mean-std-00280054.npy +3 -0
  10. 00280/img-mean-std-00280070.npy +3 -0
  11. 00280/img-mean-std-00280077.npy +3 -0
  12. 00280/img-mean-std-00280079.npy +3 -0
  13. 00280/img-mean-std-00280082.npy +3 -0
  14. 00280/img-mean-std-00280085.npy +3 -0
  15. 00280/img-mean-std-00280093.npy +3 -0
  16. 00280/img-mean-std-00280094.npy +3 -0
  17. 00280/img-mean-std-00280113.npy +3 -0
  18. 00280/img-mean-std-00280114.npy +3 -0
  19. 00280/img-mean-std-00280121.npy +3 -0
  20. 00280/img-mean-std-00280126.npy +3 -0
  21. 00280/img-mean-std-00280128.npy +3 -0
  22. 00280/img-mean-std-00280153.npy +3 -0
  23. 00280/img-mean-std-00280154.npy +3 -0
  24. 00280/img-mean-std-00280161.npy +3 -0
  25. 00280/img-mean-std-00280166.npy +3 -0
  26. 00280/img-mean-std-00280168.npy +3 -0
  27. 00280/img-mean-std-00280177.npy +3 -0
  28. 00280/img-mean-std-00280185.npy +3 -0
  29. 00280/img-mean-std-00280203.npy +3 -0
  30. 00280/img-mean-std-00280204.npy +3 -0
  31. 00280/img-mean-std-00280212.npy +3 -0
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  33. 00280/img-mean-std-00280236.npy +3 -0
  34. 00280/img-mean-std-00280238.npy +3 -0
  35. 00280/img-mean-std-00280243.npy +3 -0
  36. 00280/img-mean-std-00280244.npy +3 -0
  37. 00280/img-mean-std-00280260.npy +3 -0
  38. 00280/img-mean-std-00280271.npy +3 -0
  39. 00280/img-mean-std-00280272.npy +3 -0
  40. 00280/img-mean-std-00280276.npy +3 -0
  41. 00280/img-mean-std-00280278.npy +3 -0
  42. 00280/img-mean-std-00280292.npy +3 -0
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  49. 00280/img-mean-std-00280343.npy +3 -0
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