update point cloud process and add reminder in readme

MaverickPeter · Aug 19, 2021 · 912e18a · 912e18a
1 parent 1da7e3d
commit 912e18a
Show file tree

Hide file tree

Showing 3 changed files with 8 additions and 3 deletions.
diff --git a/README.md b/README.md
@@ -55,6 +55,11 @@ python setup.py build_ext --inplace
 
 # or install in python/site_packages
 python setup.py install
+
+# to test
+python test.py
+
+(If you meet segmentation fault error, you may have overlarge number of points to process e.g. 67w. To tackle this problem you may need to change your system stack size by 'ulimit -s 81920' in your bash)
 ```
 
 and now you will have a gputransform.cpythonxxx.so file and copy it to **[generating_queries](https://github.com/MaverickPeter/DiSCO-pytorch/tree/main/generating_queries)/[nclt](https://github.com/MaverickPeter/DiSCO-pytorch/tree/main/generating_queries/nclt) and main dir** where you can find a place holder. Note that the input of the wrapped point cloud process module you should scale the original point cloud to **[-1~1]** range for all axis. No extra process for point cloud such as downscale the points number.

diff --git a/multi-layer-polar-cython/cython/gputransform.cpython-37m-x86_64-linux-gnu.so b/multi-layer-polar-cython/cython/gputransform.cpython-37m-x86_64-linux-gnu.so
diff --git a/multi-layer-polar-cython/cython/gputransform.pyx b/multi-layer-polar-cython/cython/gputransform.pyx
@@ -6,7 +6,7 @@ assert sizeof(int) == sizeof(np.int32_t)
 
 cdef extern from "src/manager.hh":
     cdef cppclass C_GPUTransformer "GPUTransformer":
-        C_GPUTransformer(float *point, int size, int *ring, int *sector, int *height, int max_length, int num_ring, int num_sector, int num_height, int enough_large)
+        C_GPUTransformer(float *point, int size, int *ring, int *sector, int *height, int max_length, int max_height, int num_ring, int num_sector, int num_height, int enough_large)
         void transform()
         void retreive(float *point_trans)
 
@@ -16,15 +16,15 @@ cdef class GPUTransformer:
     cdef int grid_size
 
     def __cinit__(self, np.ndarray[float, ndim=1, mode = "c"] point not None,
-                    int size, int max_length, int num_ring, int num_sector, int num_height, int enough_large):
+                    int size, int max_length, int max_height, int num_ring, int num_sector, int num_height, int enough_large):
 
         self.size = size
         self.grid_size = num_ring * num_sector * num_height * enough_large
         cdef np.ndarray[int, ndim=1, mode = "c"] sector = np.zeros(self.size, dtype=np.int32)
         cdef np.ndarray[int, ndim=1, mode = "c"] ring = np.zeros(self.size, dtype=np.int32)
         cdef np.ndarray[int, ndim=1, mode = "c"] height = np.zeros(self.size, dtype=np.int32)
 
-        self.g = new C_GPUTransformer(&point[0], self.size, &ring[0], &sector[0], &height[0], max_length, num_ring, num_sector, num_height, enough_large)
+        self.g = new C_GPUTransformer(&point[0], self.size, &ring[0], &sector[0], &height[0], max_length, max_height, num_ring, num_sector, num_height, enough_large)
 
     def transform(self):
         self.g.transform()