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资源文件列表:

TEED-main.zip 大约有79个文件
  1. TEED-main/
  2. TEED-main/.idea/
  3. TEED-main/.idea/.gitignore 50B
  4. TEED-main/.idea/inspectionProfiles/
  5. TEED-main/.idea/inspectionProfiles/profiles_settings.xml 174B
  6. TEED-main/.idea/inspectionProfiles/Project_Default.xml 1.34KB
  7. TEED-main/.idea/misc.xml 270B
  8. TEED-main/.idea/modules.xml 277B
  9. TEED-main/.idea/TEED-main.iml 479B
  10. TEED-main/.idea/workspace.xml 3.4KB
  11. TEED-main/BIPED/
  12. TEED-main/checkpoints/
  13. TEED-main/checkpoints/BIPED/
  14. TEED-main/checkpoints/BIPED/0/
  15. TEED-main/checkpoints/BIPED/0/0_model.pth 243.3KB
  16. TEED-main/checkpoints/BIPED/1/
  17. TEED-main/checkpoints/BIPED/1/1_model.pth 243.3KB
  18. TEED-main/checkpoints/BIPED/2/
  19. TEED-main/checkpoints/BIPED/2/2_model.pth 243.3KB
  20. TEED-main/checkpoints/BIPED/3/
  21. TEED-main/checkpoints/BIPED/3/3_model.pth 243.3KB
  22. TEED-main/checkpoints/BIPED/4/
  23. TEED-main/checkpoints/BIPED/4/4_model.pth 243.3KB
  24. TEED-main/checkpoints/BIPED/5/
  25. TEED-main/checkpoints/BIPED/5/5_model.pth 243.3KB
  26. TEED-main/checkpoints/BIPED/6/
  27. TEED-main/checkpoints/BIPED/6/6_model.pth 243.3KB
  28. TEED-main/checkpoints/BIPED/7/
  29. TEED-main/checkpoints/BIPED/7/7_model.pth 243.3KB
  30. TEED-main/checkpoints/BIPED/events.out.tfevents.1673615094.3de84a6f18d0.29397.0 416B
  31. TEED-main/checkpoints/BIPED/pretrain_model/
  32. TEED-main/checkpoints/BIPED/pretrain_model/7_model.pth 243.3KB
  33. TEED-main/checkpoints/current_res/
  34. TEED-main/checkpoints/current_res/35028.png 58.57KB
  35. TEED-main/checkpoints/current_res/cameraman.png 100.57KB
  36. TEED-main/checkpoints/current_res/lena.png 122.09KB
  37. TEED-main/checkpoints/current_res/results.png 648.32KB
  38. TEED-main/data/
  39. TEED-main/dataset.py 22.86KB
  40. TEED-main/data/124084.jpg 62.36KB
  41. TEED-main/data/cameraman.png 121.03KB
  42. TEED-main/data/lena.tif 768.14KB
  43. TEED-main/imgs/
  44. TEED-main/imgs/teedBanner.png 1.46MB
  45. TEED-main/LICENSE 1.05KB
  46. TEED-main/loss2.py 3.35KB
  47. TEED-main/main.py 22.64KB
  48. TEED-main/README.md 2.2KB
  49. TEED-main/result/
  50. TEED-main/result/BIPED2CLASSIC/
  51. TEED-main/result/BIPED2CLASSIC/fused/
  52. TEED-main/result/BIPED2CLASSIC/fused/124084.png 65.82KB
  53. TEED-main/ted.py 10.02KB
  54. TEED-main/test1/
  55. TEED-main/test1/124084.jpg 62.36KB
  56. TEED-main/utils/
  57. TEED-main/utils/AF/
  58. TEED-main/utils/AF/Fmish.py 395B
  59. TEED-main/utils/AF/Fsmish.py 512B
  60. TEED-main/utils/AF/Xmish.py 1.01KB
  61. TEED-main/utils/AF/Xsmish.py 1.05KB
  62. TEED-main/utils/AF/__pycache__/
  63. TEED-main/utils/AF/__pycache__/Fmish.cpython-38.pyc 624B
  64. TEED-main/utils/AF/__pycache__/Fsmish.cpython-38.pyc 726B
  65. TEED-main/utils/AF/__pycache__/Xmish.cpython-38.pyc 1.42KB
  66. TEED-main/utils/AF/__pycache__/Xsmish.cpython-38.pyc 1.48KB
  67. TEED-main/utils/img_processing.py 11.32KB
  68. TEED-main/utils/train_pair0.lst 6.73MB
  69. TEED-main/utils/__pycache__/
  70. TEED-main/utils/__pycache__/img_processing.cpython-38.pyc 6.85KB
  71. TEED-main/__pycache__/
  72. TEED-main/__pycache__/dataset.cpython-38.pyc 9.14KB
  73. TEED-main/__pycache__/loss2.cpython-38.pyc 2.66KB
  74. TEED-main/__pycache__/model.cpython-38.pyc 6.91KB
  75. TEED-main/__pycache__/modelArch.cpython-38.pyc 6.92KB
  76. TEED-main/__pycache__/modelRelu.cpython-38.pyc 6.88KB
  77. TEED-main/__pycache__/modelSmishArch.cpython-38.pyc 8.09KB
  78. TEED-main/__pycache__/modelV10B2.cpython-38.pyc 7.06KB
  79. TEED-main/__pycache__/ted.cpython-38.pyc 8.74KB

资源介绍:

TEED-mainTEED-mainTEED-main
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/tiny-and-efficient-model-for-the-edge/edge-detection-on-uded)](https://paperswithcode.com/sota/edge-detection-on-uded?p=tiny-and-efficient-model-for-the-edge) # Tiny and Efficient Model for the Edge Detection Generalization (Paper) ## Overview
Tiny and Efficient Edge Detector (TEED) is a light convolutional neural network with only $58K$ parameters, less than $0.2$% of the state-of-the-art models. Training on the [BIPED](https://www.kaggle.com/datasets/xavysp/biped) dataset takes *less than 30 minutes*, with each epoch requiring *less than 5 minutes*. Our proposed model is easy to train and it quickly converges within very first few epochs, while the predicted edge-maps are crisp and of high quality, see image above. [This paper has been accepted by ICCV 2023-Workshop RCV](https://arxiv.org/abs/2308.06468). ... In construction git clone https://github.com/xavysp/TEED.git cd TEED Then, ## Testing with TEED Copy and paste your images into data/ folder, and: python main.py --choose_test_data=-1 ## Training with TEED Set the following lines in main.py: 25: is_testing =False # training with BIPED 223: TRAIN_DATA = DATASET_NAMES[0] then run python main.py Check the configurations of the datasets in dataset.py ## UDED dataset Here the [link](https://github.com/xavysp/UDED) to access the UDED dataset for edge detection ## Citation If you like TEED, why not starring the project on GitHub! [![GitHub stars](https://img.shields.io/github/stars/xavysp/TEED.svg?style=social&label=Star&maxAge=3600)](https://GitHub.com/xavysp/TEED/stargazers/) Please cite our Dataset if you find helpful in your academic/scientific publication, ``` @InProceedings{Soria_2023teed, author = {Soria, Xavier and Li, Yachuan and Rouhani, Mohammad and Sappa, Angel D.}, title = {Tiny and Efficient Model for the Edge Detection Generalization}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops}, month = {October}, year = {2023}, pages = {1364-1373} }
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