'm_scale' : 1,
'total_runs' : 10,
'max_itters' : 1000,
'min_cluster_size': 25,
'sigma' : 3
},
}
m_regular_SLIC = 1
if __name__ == '__main__':
multiprocessing.freeze_support()
#data_management.tee_out()
import os
ctx = opencl_tools.get_a_context()
#From http://stackoverflow.com/questions/3579568/choosing-a-file-in-python-simple-gui
from Tkinter import Tk
from tkFileDialog import askopenfilename, asksaveasfilename
Tk().withdraw()
file_name = askopenfilename(filetypes=[('image file','*.jpg *.png *.bmp *.tif')])
if(file_name is None or len(file_name) == 0 ):
import sys;
print("Uses quit without selecting a file");
sys.exit(0);
def __init__(self, image, queue=None):
self._image = image
if (queue is None):
self._queue = cl.CommandQueue(
opencl_tools.get_a_context(),
properties=opencl_tools.profile_properties)
else:
self._queue = queue
self._blocksize = 128
preamble = """
#define IMAGE_ROWS %d
#define IMAGE_COLS %d
#define NUMBER_COLORS %d
#define recalculate_centers_blocksize %d
#define count_center_table_locations_blocksize %d
""" % (image.shape + (self._blocksize, self._blocksize))
preamble = opencl_tools.build_preamble_for_context\
(self._queue.context,preamble)
prg = cl.Program(self._queue.context,
preamble + _SLIC_kernal_code).build()
self._find_best_center = prg.find_best_center
self._find_best_center.set_scalar_arg_dtypes([
None, #float* image_data,
None, #float* location_center,
None, #float* color_center,
None, #__global int* center_table_locations,
None, #__global int* center_table,
np.int32, #int number_of_centers,
np.float32, #float S,
np.float32, #float m,
None, #int* cluster_index,
None, #float* cluaster_distance
])
self._recalculate_centers = prg.recalculate_centers
self._recalculate_centers.set_scalar_arg_dtypes([
None, #float* image_data,
None, #int* cluster_index,
np.float32, #float S,
np.float32, #float m,
np.int32, #int number_of_clusters,
None, #float* location_center,
None, #float* color_center,
None
])
self._count_center_table_locations = prg.count_center_table_locations
self._count_center_table_locations.set_scalar_arg_dtypes([
None, #__global float* location_center,
np.float32, #float S,
np.int32, #int number_of_clusters,
None, #__global int* center_table_locations
])
self._center_table_placement = cl_scan.InclusiveScanKernel(
self._queue.context, np.int32, 'a+b', neutral='0')
self._create_center_table = prg.create_center_table
self._create_center_table.set_scalar_arg_dtypes([
None, #__global float* location_center,
None, #__global int* center_table_locations
np.float32, #float S,
np.int32, #int number_of_clusters,
None #__global float* center_table
])
self._remove_points = prg.remove_points
'total_runs': 1,
'max_itters': 1000,
'min_cluster_size': 25,
'sigma': 3
},
}
m_regular_SLIC = 1
if __name__ == '__main__':
multiprocessing.freeze_support()
import time
import glob
import os
ctx = opencl_tools.get_a_context()
# #Create an experiment
# data_management.create_experiment("eage_aware_editing");
#
# #add the source files
# source_files = glob.glob(os.path.join(os.path.dirname(__file__),'*.py'))
# dest_files = [os.path.join('source_files',os.path.basename(fi))
# for fi in source_files ]
# data_management.current_experiment().add_files(zip(source_files,dest_files))
#
# source_files = glob.glob(os.path.join(os.path.dirname(__file__),'diffution_system','*.py'))
# dest_files = [os.path.join('source_files','diffution_system',os.path.basename(fi))
# for fi in source_files ]
# data_management.current_experiment().add_files(zip(source_files,dest_files))
def __init__(self,image,queue=None):
self._image = image
if(queue is None):
self._queue = cl.CommandQueue(opencl_tools.get_a_context(),properties=opencl_tools.profile_properties)
else:
self._queue = queue
self._blocksize = 128;
preamble = """
#define IMAGE_ROWS %d
#define IMAGE_COLS %d
#define NUMBER_COLORS %d
#define recalculate_centers_blocksize %d
#define count_center_table_locations_blocksize %d
""" % (image.shape + (self._blocksize,self._blocksize))
preamble = opencl_tools.build_preamble_for_context\
(self._queue.context,preamble)
prg = cl.Program(self._queue.context,preamble + _SLIC_kernal_code).build();
self._find_best_center = prg.find_best_center
self._find_best_center.set_scalar_arg_dtypes([
None, #float* image_data,
None, #float* location_center,
None, #float* color_center,
None, #__global int* center_table_locations,
None, #__global int* center_table,
np.int32, #int number_of_centers,
np.float32, #float S,
np.float32, #float m,
None, #int* cluster_index,
None, #float* cluaster_distance
])
self._recalculate_centers = prg.recalculate_centers
self._recalculate_centers.set_scalar_arg_dtypes([
None, #float* image_data,
None, #int* cluster_index,
np.float32, #float S,
np.float32, #float m,
np.int32, #int number_of_clusters,
None, #float* location_center,
None, #float* color_center,
None
])
self._count_center_table_locations = prg.count_center_table_locations
self._count_center_table_locations.set_scalar_arg_dtypes([
None,#__global float* location_center,
np.float32,#float S,
np.int32,#int number_of_clusters,
None,#__global int* center_table_locations
])
self._center_table_placement = cl_scan.InclusiveScanKernel(self._queue.context,
np.int32,
'a+b',
neutral='0')
self._create_center_table = prg.create_center_table
self._create_center_table.set_scalar_arg_dtypes([
None,#__global float* location_center,
None,#__global int* center_table_locations
np.float32,#float S,
np.int32,#int number_of_clusters,
None#__global float* center_table
])
self._remove_points = prg.remove_points
