1. 17 Mar, 2020 1 commit
  2. 16 Mar, 2020 2 commits
  3. 13 Mar, 2020 2 commits
  4. 12 Mar, 2020 6 commits
  5. 11 Mar, 2020 7 commits
  6. 10 Mar, 2020 14 commits
  7. 09 Mar, 2020 4 commits
    • Alexander Alekhin's avatar
      27b71d63
    • Alexander Alekhin's avatar
    • NesQl's avatar
      Merge pull request #16724 from liqi-c:3.4-tengine · 0bcdf7d0
      NesQl authored
      * Add Tengine support .
      
      * Modify printf to CV_LOG_WARNING
      
      * a few minor fixes in the code
      
      * Renew Tengine version
      
      * Add header file for CV_LOG_WARNING
      
      * Add #ifdef HAVE_TENGINE in tengine_graph_convolution.cpp
      
      * remove trailing whitespace
      
      * Remove trailing whitespace
      
      * Modify for compile problem
      
      * Modify some code style error
      
      * remove whitespace
      
      * Move some code style problem
      
      * test
      
      * add ios limit and build problem
      
      * Modified as alalek suggested
      
      * Add cmake 2.8 support
      
      * modify cmake 3.5.1 problem
      
      * test and set BUILD_ANDROID_PROJECTS OFF
      
      * remove some compile error
      
      * remove some extra code in tengine
      
      * close test.
      
      * Test again
      
      * disable android.
      
      * delete ndk version judgement
      
      * Remove setenv() call . and add License information
      
      * Set tengine default OFF. Close test .
      Co-authored-by: 's avatarVadim Pisarevsky <vadim.pisarevsky@gmail.com>
      0bcdf7d0
    • Alexander Duda's avatar
      calib3d: add estimateChessboardSharpness · 44560c3e
      Alexander Duda authored
      Image sharpness, as well as brightness, are a critical parameter for
      accuracte camera calibration. For accessing these parameters for
      filtering out problematic calibraiton images, this method calculates
      edge profiles by traveling from black to white chessboard cell centers.
      Based on this, the number of pixels is calculated required to transit
      from black to white. This width of the transition area is a good
      indication of how sharp the chessboard is imaged and should be below
      ~3.0 pixels.
      
      Based on this also motion blur can be detectd by comparing sharpness in
      vertical and horizontal direction. All unsharp images should be excluded
      from calibration as they will corrupt the calibration result. The same
      is true for overexposued images due to a none-linear sensor response.
      This can be detected by looking at the average cell brightness of the
      detected chessboard.
      44560c3e
  8. 07 Mar, 2020 2 commits
  9. 06 Mar, 2020 2 commits