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07-bloom_filter.py
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# -*- coding: utf-8 -*-
from __future__ import absolute_import, print_function
import numpy as np
import pyopencl as cl
import cv2
from PIL import Image
def RoundUp(groupSize, globalSize):
r = globalSize % groupSize;
if r == 0:
return globalSize
else:
return globalSize + groupSize - r
# 创建Context
# 如果有多个设备，则会提示选择
ctx = cl.create_some_context()
# 创建CommandQueue
queue = cl.CommandQueue(ctx)
mf = cl.mem_flags
# 通过字符串内容编译OpenCL的Program
prg = cl.Program(ctx, """
__kernel void bloom_filter(__read_only image2d_t input,
__write_only image2d_t output){
const sampler_t sampler = CLK_FILTER_NEAREST |
CLK_NORMALIZED_COORDS_FALSE |
CLK_ADDRESS_CLAMP_TO_EDGE;
const int2 size = get_image_dim(input);
float2 coord = (float2)(get_global_id(0),get_global_id(1));
float4 sum = (float4)(0.0f,0.0f,0.0f,0.0f);
float a = 0.15f;
float g = 0.15f;
float e = 0.25f;
float b = 0.25f;
float f = 0.35f;
float c = 0.55f;
float d = 0.45f;
sum += read_imagef(input,sampler,coord + (float2)(-3,-4) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,-3) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-4,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,-2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-4,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,-1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-4,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,0) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-4,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,1) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-4,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-3,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-2,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-1,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(-0,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(1,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(2,2) * a) * g;
sum += read_imagef(input,sampler,coord + (float2)(3,2) * a) * g;
float4 color = read_imagef(input,sampler,coord);
if(color.x < e){
float4 rgba = sum * sum * b + color;
rgba.w = 1.0f;
write_imagef(output,convert_int2(coord),rgba);
}else{
if(color.x < f){
float4 rgba = sum * sum * c + color;
rgba.w = 1.0f;
write_imagef(output,convert_int2(coord),rgba);
}else{
float4 rgba = sum * sum * d + color;
rgba.w = 1.0f;
write_imagef(output,convert_int2(coord),rgba);
}
}
}
""").build()
# 打开图片文件
src1 = Image.open('temp/images/f2.png')
print(src1.size)
dist = Image.new('RGBA',(640,480),(255,255,255))
# OpenCL处理的图片文件格式RGBA,unit8
imageFormat = cl.ImageFormat(cl.channel_order.RGBA,cl.channel_type.UNSIGNED_INT8)
# 将图片从Host复制到Device
img1 = cl.Image(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR,imageFormat,src1.size,None,src1.tobytes())
output = cl.Image(context=ctx,flags=mf.WRITE_ONLY,format=imageFormat,shape=src1.size)
# 根据图片大小定义WorkSize
localWorkSize = ( 8, 8 )
globalWorkSize = ( RoundUp(localWorkSize[0], src1.size[0]),
RoundUp(localWorkSize[1], src1.size[1]))
# 执行Kernel
prg.bloom_filter(queue,globalWorkSize,localWorkSize,img1,output)
buffer = np.zeros(src1.size[0] * src1.size[1] * 4, np.uint8)
origin = ( 0, 0, 0 )
region = ( src1.size[0], src1.size[1], 1 )
# 将处理好的图片从设备复制到HOST
cl.enqueue_read_image(queue, output,
origin, region, buffer).wait()
# 保存图片
dist = Image.frombytes("RGBA",src1.size, buffer.tobytes())
dist.save('temp/images/cl-output.png')
dist.show()