1. 17 12月, 2020 4 次提交
  2. 27 11月, 2020 1 次提交
  3. 24 11月, 2020 1 次提交
    • W
      [Dygraph] train and eval yolov3 successfully (#1753) · 19eb7f47
      wangxinxin08 提交于
      * split yolov3 loss using paddle op
      
      * add sync_bn and modify list to LayerList to use sync_bn, add missing op, support cutmix op in dataset, modify reader to use new ops
      
      * modify code according to review
      
      * modify code to run eval.py successfully
      
      * modify code to run eval and train successfully
      
      * modify code to use mixup
      
      * rebase code on lastest dygraph
      
      * modify code to run in sync_bn mode
      
      * modify code according to review
      
      * modify target size of ResizeOp
      19eb7f47
  4. 23 11月, 2020 1 次提交
  5. 12 11月, 2020 1 次提交
  6. 10 11月, 2020 1 次提交
  7. 31 8月, 2020 1 次提交
  8. 27 8月, 2020 1 次提交
  9. 21 7月, 2020 1 次提交
  10. 27 5月, 2020 1 次提交
  11. 07 5月, 2020 1 次提交
  12. 22 4月, 2020 1 次提交
  13. 07 4月, 2020 1 次提交
  14. 04 2月, 2020 1 次提交
  15. 23 12月, 2019 1 次提交
  16. 19 12月, 2019 1 次提交
    • Q
      Polish reader to simplify preprocessing logic. (#112) · 8192c758
      qingqing01 提交于
      * Polish Reader to simplify preprocessing logic.
      #  sample_transforms-> make batch -> batch_transforms in Reader.
      * Clean some code
      * Imporve yolov3_r50vd_dcn_obj365_pretrained_coco 41.4 to 41.8.
      * Update all configs.
      8192c758
  17. 14 10月, 2019 1 次提交
  18. 31 7月, 2019 1 次提交
  19. 29 7月, 2019 1 次提交
    • K
      Add Yolov3 model based on PascalVOC and add voc metrics by Python. (#2801) · b00deb54
      Kaipeng Deng 提交于
      * add voc_eval and yolo_darknet_voc
      
      * add yolov3_darknet_voc in MODEL_ZOO
      
      * fix default im_size
      
      * fix MODEL_ZOO note
      
      * fix is_bbox_normalized
      
      * extract map to map_utils.py
      
      * update yolov3_dorknet_voc mixup
      
      * add yolov3_r34_voc
      
      * add yolov3_mobilenet_v1_voc
      
      * fix drop empty in VAL mode
      
      * use cfg.num_classes
      
      * assert metric valid
      
      * enable difficulty can be None
      
      * add comment for bbox_eval
      
      * num_classes in retinanet
      b00deb54
  20. 28 6月, 2019 1 次提交