Hi! Thanks for great work!
I wonder how to organized the training data (floorplan.npy , segmentation).
I have a few questions in this regard.
Dose floorplan.npy consist of actual scale?
I think find_nearest_segment is considering the acutal wall_pcd scale, it that right?
Can you tell me how to make a custom floorplan.npy?
Can I get frame-wall.png and frame-floor.png , the reseult of segmantation, by applying RGB images to MSeg as mentioned in the paper?
Yes, floorplan.npy is a plan in actual scale. It should contain the 2D coordinates of the edges of the scene plan (Nx4 array, each row is (p_1, p_2), where p_1, p_2 are the @d coordinates of two vertices (corners) connected by the edge (wall)
Yes, frame-wall.png and frame-floor.png may be obtained by applyong any segmentation algorithm, for example, MSeg.
Hi! Thanks for great work! I wonder how to organized the training data (floorplan.npy , segmentation). I have a few questions in this regard.
Dose floorplan.npy consist of actual scale? I think find_nearest_segment is considering the acutal wall_pcd scale, it that right? Can you tell me how to make a custom floorplan.npy?
Can I get frame-wall.png and frame-floor.png , the reseult of segmantation, by applying RGB images to MSeg as mentioned in the paper?
Thank you.