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mx-maskrcnn-master

于 2020-06-17 发布
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下载积分: 1 下载次数: 5

代码说明:

说明:  我们提出了一个简单、灵活和通用的对象实例分割框架。我们的方法能有效检测图像中的对象,同时为每个实例生成高质量的 segmentation mask。这种被称为 Mask R-CNN 的方法通过添加用于预测 object mask 的分支来扩展 Faster R-CNN,该分支与用于边界框识别的现有分支并行。Mask R-CNN 训练简单,只需在以 5fps 运行的 Faster R-CNN 之上增加一个较小的 overhead。此外,Mask R-CNN 很容易推广到其他任务,例如它可以允许同一个框架中进行姿态估计。我们在 COCO 系列挑战的三个轨道任务中均取得了最佳成果,包括实例分割、边界对象检测和人关键点检测。没有任何 tricks,Mask R-CNN 的表现优于所有现有的单一模型取得的成绩,包括 COCO 2016 挑战赛的冠军。(Mask R-CNN code by HeKaiming)

文件列表:

mx-maskrcnn-master, 0 , 2018-02-28
mx-maskrcnn-master\.gitignore, 988 , 2018-02-28
mx-maskrcnn-master\.gitmodules, 103 , 2018-02-28
mx-maskrcnn-master\LICENSE, 11357 , 2018-02-28
mx-maskrcnn-master\Makefile, 221 , 2018-02-28
mx-maskrcnn-master\README.md, 5451 , 2018-02-28
mx-maskrcnn-master\data, 0 , 2018-02-28
mx-maskrcnn-master\data\cityscape, 0 , 2018-02-28
mx-maskrcnn-master\data\cityscape\imglists, 0 , 2018-02-28
mx-maskrcnn-master\data\cityscape\imglists\test.lst, 200205 , 2018-02-28
mx-maskrcnn-master\data\cityscape\imglists\train.lst, 412545 , 2018-02-28
mx-maskrcnn-master\data\cityscape\imglists\val.lst, 67790 , 2018-02-28
mx-maskrcnn-master\demo_mask.py, 2115 , 2018-02-28
mx-maskrcnn-master\eval_maskrcnn.py, 2113 , 2018-02-28
mx-maskrcnn-master\figures, 0 , 2018-02-28
mx-maskrcnn-master\figures\maskrcnn_result.png, 900697 , 2018-02-28
mx-maskrcnn-master\figures\test.jpg, 40967 , 2018-02-28
mx-maskrcnn-master\incubator-mxnet, 0 , 2018-02-28
mx-maskrcnn-master\rcnn, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align-inl.h, 8596 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align.cc, 2824 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align.cu, 12308 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align_v1-inl.h, 15877 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align_v1.cc, 3090 , 2018-02-28
mx-maskrcnn-master\rcnn\CXX_OP\roi_align_v1.cu, 446 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP\fpn_roi_pooling.py, 4584 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP\mask_output.py, 1971 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP\mask_roi.py, 2240 , 2018-02-28
mx-maskrcnn-master\rcnn\PY_OP\proposal_fpn.py, 8149 , 2018-02-28
mx-maskrcnn-master\rcnn\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\config.py, 5104 , 2018-02-28
mx-maskrcnn-master\rcnn\core, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\core\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\core\callback.py, 1710 , 2018-02-28
mx-maskrcnn-master\rcnn\core\loader.py, 24515 , 2018-02-28
mx-maskrcnn-master\rcnn\core\metric.py, 9044 , 2018-02-28
mx-maskrcnn-master\rcnn\core\module.py, 8588 , 2018-02-28
mx-maskrcnn-master\rcnn\core\solver.py, 3136 , 2018-02-28
mx-maskrcnn-master\rcnn\core\tester.py, 13716 , 2018-02-28
mx-maskrcnn-master\rcnn\cython, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\.gitignore, 15 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\anchors.pyx, 1185 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\bbox.pyx, 1763 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\cpu_nms.pyx, 2241 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\gpu_nms.hpp, 146 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\gpu_nms.pyx, 1110 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\nms_kernel.cu, 5064 , 2018-02-28
mx-maskrcnn-master\rcnn\cython\setup.py, 5515 , 2018-02-28
mx-maskrcnn-master\rcnn\dataset, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\dataset\__init__.py, 53 , 2018-02-28
mx-maskrcnn-master\rcnn\dataset\cityscape.py, 12991 , 2018-02-28
mx-maskrcnn-master\rcnn\dataset\ds_utils.py, 442 , 2018-02-28
mx-maskrcnn-master\rcnn\dataset\imdb.py, 13205 , 2018-02-28
mx-maskrcnn-master\rcnn\io, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\io\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\io\image.py, 5850 , 2018-02-28
mx-maskrcnn-master\rcnn\io\rcnn.py, 19628 , 2018-02-28
mx-maskrcnn-master\rcnn\io\rpn.py, 10379 , 2018-02-28
mx-maskrcnn-master\rcnn\io\threaded_loader.py, 20199 , 2018-02-28
mx-maskrcnn-master\rcnn\processing, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\assign_levels.py, 1221 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\bbox_regression.py, 9983 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\bbox_transform.py, 5023 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\generate_anchor.py, 2443 , 2018-02-28
mx-maskrcnn-master\rcnn\processing\nms.py, 1414 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\UPSTREAM_REV, 80 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\__init__.py, 21 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\_mask.pyx, 11430 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\coco.py, 18296 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\cocoeval.py, 23849 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\mask.py, 4570 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\maskApi.c, 8249 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\maskApi.h, 2176 , 2018-02-28
mx-maskrcnn-master\rcnn\pycocotools\setup.py, 579 , 2018-02-28
mx-maskrcnn-master\rcnn\symbol, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\symbol\__init__.py, 30 , 2018-02-28
mx-maskrcnn-master\rcnn\symbol\symbol_mask_fpn.py, 33269 , 2018-02-28
mx-maskrcnn-master\rcnn\tools, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\demo_maskrcnn.py, 4732 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\demo_single_image.py, 6421 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\test_maskrcnn.py, 4730 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\test_rpn.py, 4318 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\train_maskrcnn.py, 9777 , 2018-02-28
mx-maskrcnn-master\rcnn\tools\train_rpn.py, 9360 , 2018-02-28
mx-maskrcnn-master\rcnn\utils, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\utils\__init__.py, 0 , 2018-02-28
mx-maskrcnn-master\rcnn\utils\combine_model.py, 709 , 2018-02-28
mx-maskrcnn-master\rcnn\utils\load_data.py, 1718 , 2018-02-28
mx-maskrcnn-master\rcnn\utils\load_model.py, 1999 , 2018-02-28
mx-maskrcnn-master\rcnn\utils\save_model.py, 762 , 2018-02-28
mx-maskrcnn-master\scripts, 0 , 2018-02-28
mx-maskrcnn-master\scripts\demo.sh, 509 , 2018-02-28
mx-maskrcnn-master\scripts\demo_single_image.sh, 432 , 2018-02-28

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    自适应波束形成的三个准则:MMSELCMVMSINR(Three criteria for adaptive beamforming: MMSELCMVMSINR)
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