1. 23 1月, 2019 1 次提交
  2. 27 12月, 2018 1 次提交
  3. 29 10月, 2018 1 次提交
  4. 20 9月, 2018 2 次提交
  5. 21 8月, 2018 1 次提交
  6. 14 8月, 2018 1 次提交
    • M
      Add MKL-DNN benchmarking for chinese_ner (#1048) · f36588dc
      Michał Gallus 提交于
      * Add MKL-DNN Benchmarking to CRNN-CTC
      
      * Add MKL-DNN benchmarking for chinese_ner
      
      * Make crnn-ctc scripts more portable
      
      * Merge CRNN-CTC train & inference scripts
      
      * Remove LD_LIBRARY_PATH from crnn-ctc scripts
      
      * CRNN-CTC scripts: set parallel to true
      
      Abort script if batch_size is lower than num of cores
      
      * CRNN-CTC scripts: limit mode options in infer
      
      * CRNN-CTC scripts: set mkldnn parallel to False
      
      * CRNN-CTC scripts: remove mkldnn parallel warning
      
      * Chinese-ner: Merge train & infer scripts, update readme
      
      * Chinese_ner: add --parallel flag for train
      f36588dc
  7. 04 6月, 2018 3 次提交
  8. 27 4月, 2018 1 次提交
    • X
      COCO dataset for SSD and update README.md (#844) · c92deba1
      Xingyuan Bu 提交于
      * ready to coco_reader
      
      * complete coco_reader.py & coco_train.py
      
      * complete coco reader
      
      * rename file
      
      * use argparse instead of explicit assignment
      
      * fix
      
      * fix reader bug for some gray image in coco data
      
      * ready to train coco
      
      * fix bug in test()
      
      * fix bug in test()
      
      * change coco dataset to coco2017 dataset
      
      * change dataset from coco to coco2017
      
      * change learning rate
      
      * fix bug in gt label (category id 2 label)
      
      * fix bug in background label
      
      * save model when train finished
      
      * use coco map
      
      * adding coco year version args: 2014 or 2017
      
      * add coco dataset download, and README.md
      
      * fix
      
      * fix image truncted IOError, map version error
      
      * add test config
      
      * add eval.py for evaluate trained model 
      
      * fix
      
      * fix bug when cocoMAP
      
      * updata READEME.md
      
      * fix cocoMAP bug
      
      * find strange with test_program = fluid.default_main_program().clone(for_test=True)
      
      * add inference and visualize, awa, README.md
      
      * upload infer&visual example image
      
      * refine image
      
      * refine
      
      * fix bug after merge
      
      * follow yapf
      
      * follow comments
      
      * fix bug after separate eval and eval_cocoMAP
      
      * follow yapf
      
      * follow comments
      
      * follow yapf
      
      * follow yapf
      c92deba1