According to https://github.com/balcilar/DenseDepthMap/blob/3589873ce2d9426302ba900e51f9568132ff9bb1/dense_depth_map.m, the snippet here:

The essence of creating dense depth map is to calculate weighted depth information according to the distance of neighborhood. The original repo is based on inverse distance weighted. When it comes to the distance calculation, I have mads some adjustments, replacing the np.round() with np.int32(). Also, in the double loop statements, I have deleted - grid - 1.
`

  def dense_map(Pts, n, m, grid):
      ng = 2 * grid + 1
      mX = np.zeros((m,n)) + np.float("inf")
      mY = np.zeros((m,n)) + np.float("inf")
      mD = np.zeros((m,n))
      mX[np.int32(Pts[1]),np.int32(Pts[0])] = Pts[0] - np.int32(Pts[0])#np.round(Pts[0])  # NOTICE
      mY[np.int32(Pts[1]),np.int32(Pts[0])] = Pts[1] - np.int32(Pts[1])#np.round(Pts[1])  # NOTICE
      mD[np.int32(Pts[1]),np.int32(Pts[0])] = Pts[2]
      
      KmX = np.zeros((ng, ng, m - ng, n - ng))
      KmY = np.zeros((ng, ng, m - ng, n - ng))
      KmD = np.zeros((ng, ng, m - ng, n - ng))
      
      for i in range(ng):
          for j in range(ng):
              KmX[i,j] = mX[i : (m - ng + i), j : (n - ng + j)] + i #- grid - 1  # NOTICE
              KmY[i,j] = mY[i : (m - ng + i), j : (n - ng + j)] + j #- grid - 1  # NOTICE
              KmD[i,j] = mD[i : (m - ng + i), j : (n - ng + j)]
      S = np.zeros_like(KmD[0,0])
      Y = np.zeros_like(KmD[0,0])

      # Inverse distance weighted
      for i in range(ng):
          for j in range(ng):
              s = 1/np.sqrt(KmX[i,j] * KmX[i,j] + KmY[i,j] * KmY[i,j])
              Y = Y + s * KmD[i,j]
              S = S + s
      
      S[S == 0] = 1
      out = np.zeros((m,n))
      out[grid + 1 : -grid, grid + 1 : -grid] = Y/S
      return out

`

Hi, I saw your impressive work and am curious, is it possible to project back the estimated dense depth map to point cloud coordinates? if so, can you please provide a code for that? Thanks in advance.

There is not input file path, where should I run this code? please help me out to do this, since this is my first time. Thanks a lot !

It showing some syntax error, can you please help me to solve this error ? and how can i visualize the output ?

Hi, thanks for sharing the code.
I have some problems with the code in depth_map.py.
To deal with images in sequence 04 where the size is 370 * 1226,
the error is located in line 10:
mX[np.int32(Pts[1]),np.int32(Pts[0])] = Pts[0] - np.round(Pts[0])
IndexError: index 370 is out of bounds for axis 0 with size 370

I found that the value of Pts[1] is larger than 370 and the value of Pts[0] is larger than 1226, so there is an index error.
The calib.txt is correct because sequences 00,01,02,03 can be done well.
Can you give some suggestions? Thanks very much.