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AI4quant 2018 PIXNET Hackathon

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Jason joined 2018 PIXNET Hackathon Food-AI 智慧影像生成
https://github.com/pixnet/2018-pixnet-hackathon/tree/master/food-ai

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AI4quant 2018 PIXNET Hackathon

  1. 1. Copyright © 2018 by AI4quant [TW] All rights reserved AI4quant: AI智慧影像生成 PIXNET Hackathon 2018 Jason Chuang、呂沂樺、Kiki 2018-08-19
  2. 2. Copyright © 2018 by AI4quant [TW] All rights reserved What is AI? Big Data Algorithm Computing Power
  3. 3. Copyright © 2018 by AI4quant [TW] All rights reserved Data preprocessing for training data We use 5 different datasets for training If the shortest width of the image is less than 256 pixels, ignore Shrink the shortest width to 256 pixels, cut the center part of the image
  4. 4. Copyright © 2018 by AI4quant [TW] All rights reserved Big data Food-11: https://mmspg.epfl.ch/food-image-datasets DataSet Size(jpg, png) Number of Files # Training files Training size(bmp, 256x256) # Validation files dataset100 1GB 14,467 10,044 1.83GB 0 dataset256 4GB 31,653 27,002 5GB 0 Food-11 1.1GB 16,643 16,635 3.04GB 0 food-101 4.76GB 101,008 100,956 18.4GB 0 pixfood20 2.03GB 31,305 19,322 3.53GB 19,322
  5. 5. Copyright © 2018 by AI4quant [TW] All rights reserved Algorithms are motivated by research paper DCNN based method Image Inpainting for Irregular Holes Using Partial Convolutions, 2018, Guilin Liu, Fitsum A. Reda, Kevin J. Shih, Ting-Chun Wang, Andrew Tao, Bryan Catanzaro High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis, 2017, Chao Yang, Xin Lu,Zhe Lin, Eli Shechtman, Oliver Wang, and Hao Li Style Transfer (Harmonization) A Neural Algorithm of Artistic Style, 2015, Leon A. Gatys, Alexander S. Ecker, Matthias Bethge
  6. 6. Copyright © 2018 by AI4quant [TW] All rights reserved Proposed model#1 - PConv Hole mask: random shape
  7. 7. Copyright © 2018 by AI4quant [TW] All rights reserved U-net like architecture(encoder-decoder)
  8. 8. Copyright © 2018 by AI4quant [TW] All rights reserved PConv:During prediction-Erosion
  9. 9. Copyright © 2018 by AI4quant [TW] All rights reserved Proposed model#2: Content network- central square Model : pre-trained imagenet_inpaintCenter.t7
  10. 10. Copyright © 2018 by AI4quant [TW] All rights reserved Final image: Image blending g(x)=(1-ß)*f1(x)+ß*f2(x) ß is (0,1)
  11. 11. Copyright © 2018 by AI4quant [TW] All rights reserved Code library and computation platform ● Tensorflow 1.9.0 ● Keras 2.2.2 ● OpenCV 3.4.0 ● Torch Training(Oregon, U.S.) Model Evaluation/Competition (GCP in Taiwan) ● AWS p3.2xlarge ● Nvidia V100 GPU ● 8vCPU ● 61GB memory ● GCP Google Compute Engine ● Nvidia K80 GPU ● 4 vCPU ● 26 GB memory
  12. 12. Copyright © 2018 by AI4quant [TW] All rights reserved Quantitative comparison(validation data loss)
  13. 13. Copyright © 2018 by AI4quant [TW] All rights reserved Qualitative comparison
  14. 14. Copyright © 2018 by AI4quant [TW] All rights reserved During prediction - Deep style transfer(harmonization) (Thinking to use) Iter 0 Iter 5 Iter 10

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