标签(空格分隔): C/C++ python python调用C 人工智能 AI
-
python访问C/C++
- python的底层大部分都是C/C++实现,python和C和C++具有天然的互相调用优势;
- 很多核心的算法库都是C/C++写的,在python开发过程中,经常访问别人的动态库;
- 知名人工智能(深度学习)框架训练系统都是python写的,而运行时一般都是以动态库的形式提供;
-
python访问C/C++的方式
- ctypes;
- pybind11;
- cffi
- swig
-
ctypes的优势
- 不要修改动态库的源码;
- 只需要动态库和头文件;
- 使用比较简单,而且目前大部分库都是兼容C/C++;
本文以一个典型的深度学习(人工智能AI)的图像检测的python自动化测试,介绍ctypes的使用;
-
ctypes的使用
结构体头文件:
//
// Created by yinlib on 18-12-4.
//
#ifndef CVIMAGETEST_CV_COMMON_H
#define CVIMAGETEST_CV_COMMON_H
#ifdef __MSC_VER
# define CV_IMAGE_API_ __declspec(dllexport)
#else
# define CV_IMAGE_API_ __attribute__((visibility("default")))
#endif
#ifdef __cplusplus
# define CV_IMAGE_API extern "C" CV_IMAGE_API_
#else
# define CV_IMAGE_API CV_IMAGE_API_
#endif
#define RC_OK 0
#define RC_E_HANDLE -1
#define RC_E_INVALIDARG -2
#define RC_E_OUTOFMEMORY -3
#define RC_E_INVALID_FORMAT -4
#define RC_E_FAIL -5
typedef void *mt_handle_t;
typedef int mt_result_t;
typedef struct rect_t{
int left;
int top;
int right;
int bottom;
} rect_t;
typedef struct point3f_t{
float x;
float y;
float z;
}point_t;
typedef struct extra_info_t{
float mvp_mat[3][3];
point_t *points_ori;
int point_count;
}extra_info_t;
typedef struct detection_result_t{
rect_t rect;
float score;
int label;
int orientation;
extra_info_t extra_info;
} detection_result_t;
#endif //CVIMAGETEST_CV_COMMON_H
接口头文件:
#pragma once
#include "mt_image_common.h"
CV_IMAGE_API
mt_result_t
mt_image_detect_init_config(const char* congif);
CV_IMAGE_API
mt_result_t
mt_image_detect_create(const char* model_path, mt_handle_t* handle);
CV_IMAGE_API
void
mt_image_detect_destroy(mt_handle_t handle);
CV_IMAGE_API
void
mt_image_release_detect_result(detection_result_t* detection_result, int count);
CV_IMAGE_API
mt_result_t
mt_image_detect_compact(mt_handle_t handle, const unsigned char* img, int format, int image_width,
int image_height, int image_stride, detection_result_t** detect_info, int* count);
CV_IMAGE_API
mt_result_t
mt_image_detect_reset(mt_handle_t handle);
结构体的映射:
from ctypes import *
import os
import shutil
class rect_t(Structure):
pass
rect_t._fields_ = [
('left', c_int),
('top', c_int),
('right', c_int),
('bottom', c_int),
]
class point3f_t(Structure):
pass
point3f_t._fields_ = [
('x', c_float),
('y', c_float),
('z', c_float),
]
class extra_info(Structure):
pass
extra_info._fields_ = [
('mvp_mat', c_float*3*3),
('point_t', POINTER(point3f_t)),
('point_count', c_int),
]
class detection_result(Structure):
pass
detection_result._fields_ = [
('rect', rect_t),
('score', c_float),
('label', c_int),
('orientation', c_int),
('extra_info', extra_info),
]
def movefile(srcpath, dstpath):
if not os.path.isfile(srcpath):
print(srcpath + ' is not exist!')
else:
fpath, fname = os.path.split(dstpath)
if not os.path.exists(fpath):
os.makedirs(fpath)
shutil.copy(srcpath, dstpath)
print('copy ' + srcpath + '->' + dstpath)
接口映射:
import ctypes
import os
class MtLibrary:
def __init__(self, path):
self.path = path
self.lib = None
self.hasInit = False
def load_library(self):
dl = ctypes.cdll.LoadLibrary
print('load_library lib is Exist : ' + str(os.path.exists(self.path)))
print(os.getcwd())
lib = dl(self.path)
self.lib = lib
self.hasInit = True
def init_license(self, licence):
if not self.hasInit:
print('lib has not init!!')
return False
licence_context = bytes(licence, "utf8")
return self.lib.mt_image_detect_init_config(licence_context)
def create_handle(self, path, handle):
if not self.hasInit:
print('lib has not init!!')
return None
return self.lib.mt_image_detect_create(path, handle)
def reset_handle(self, handle):
return self.lib.mt_image_detect_reset(handle)
def detect_image(self, handle, image, format, width, height, stride, detect_info, count):
if not self.hasInit:
print('lib has not init!!')
return None
return self.lib.mt_image_detect_compact(handle, image, format, width, height, stride, detect_info, count)
def release_result(self, detect_result, count):
if not self.hasInit:
print("lib has not init!!")
return None
return self.lib.mt_image_release_detect_result(detect_result, count)
def destroy_handle(self, handle):
if not self.hasInit:
print("lib has not init!!")
return None
return self.lib.mt_image_detect_destroy(handle)
重点问题:
- 结构体和复杂结构提的映射
C中的结构体
typedef struct extra_info_t{
float mvp_mat[3][3];
point_t *points_ori;
int point_count;
}extra_info_t;
typedef struct detection_result_t{
rect_t rect;
float score;
int label;
int orientation;
extra_info_t extra_info;
} detection_result_t;
Python中的类
class extra_info(Structure):
pass
extra_info._fields_ = [
('mvp_mat', c_float*3*3),
('point_t', POINTER(point3f_t)),
('point_count', c_int),
]
class detection_result(Structure):
pass
detection_result._fields_ = [
('rect', rect_t),
('score', c_float),
('label', c_int),
('orientation', c_int),
('extra_info', extra_info),
]
多维数组
float mvp_mat[3][3] --> c_float33
数组指针
point_t *points_ori --> POINTER(point3f_t)
- 调用时指针(二级指针)的映射
CV_IMAGE_API
mt_result_t
mt_image_detect_compact(mt_handle_t handle, const unsigned char* img, int format, int image_width,
int image_height, int image_stride, detection_result_t** detect_info, int* count);
python调用:
TARGETPOINTER_t = POINTER(detection_result)
result_handle = TARGETPOINTER_t()
print('result_handle: ' + str(result_handle))
count = c_int(0)
status = mt_image_detect.detect_image(handle, byref(image_data), 0, width, height, width * 3, byref(result_handle), pointer(count))
print('detect_image status: ' + str(status) + " count : " + str(count.value))
detect_content = result_handle.contents
针对于二级指针,必须POINTER(detection_result)生成T*,然后创建result_handle = TARGETPOINTER_t(),然后通过byref(result_handle)得到二级指针
- byref(n)返回的相当于C的指针右值&n,本身没有被分配空间;
- pointer返回的相当于指针左值T* p=&n,可以改变,可以取地址; POINTER得到是类;
调用结果
/home/sensetime/miniconda3/envs/pythonPIL/bin/python /home/sensetime/jayzwang/workspace/clion_workspace/PyImageTest/image_test.py
copy ../CvImageTest/build/libmtimage.so->./extents/libs/libmtimage.so
copy ../CvImageTest/mt_image_common.h->./extents/include/mt_image_common.h
copy ../CvImageTest/mt_image_detect.h->./extents/include/mt_image_detect.h
test license
load_library lib is Exist : True
/home/sensetime/jayzwang/workspace/clion_workspace/PyImageTest
mt_image_detect_init_config.14: in
init_license : 0
mt_image_detect_create.24: in
create_handle : 0 handle : c_long(94128605088976)
pil image : 768 height : 576
width : 768 height : 576 format : None
image pointer : <cparam 'P' (0x559c061f1960)> image_date [-1] : 255
result_handle: <__main__.LP_detection_result object at 0x7fd92de1d1e0>
mt_image_detect_compact.62: in
mt_image_detect_compact.75: mt_image_detect_compact : 0x559c060ce080
detect_image status: 0 count : 1
detect result left : 20
detect result label: 1
detect result points: 1
mt_image_detect_reset.82: in
reset_handle status: 0
mt_image_release_detect_result.46: in
mt_image_detect_destroy.34: in
destroy_handle status: 0 handle : c_long(94128605088976)
其他:
- 文件移动
def movefile(srcpath, dstpath):
if not os.path.isfile(srcpath):
print(srcpath + ' is not exist!')
else:
fpath, fname = os.path.split(dstpath)
if not os.path.exists(fpath):
os.makedirs(fpath)
shutil.copy(srcpath, dstpath)
print('copy ' + srcpath + '->' + dstpath)
- 图片读取和转码,使用pil读取,并转换成BGR(AI/深度学习的大部分输入都是BGR)
hand_image = Image.open('./extents/test_image/timg.jpeg')
hand_image = hand_image.convert('RGB')
width, height = hand_image.size
image_format = hand_image.format
image_data = (c_ubyte * (width * height * 3))()
print('pil image : ' + str(width) + " height : " + str(height))
# hand_image.show()
for x in range(height):
for y in range(width):
r, g, b = hand_image.getpixel((y, x))
#bgr = b, g, r
image_data[(x * width + y)*3] = b
image_data[(x * width + y)*3 + 1] = g
image_data[(x * width + y)*3 + 2] = r
- 写文件
out_file = open('image_in', 'wb')
out_file.write(image_data)
out_file.close()
结语:
ctypes是非常轻量级的python调用C/C++的框架,非常适用于第三库的测试,运行.能够快速实现自动化测试,压力测试等,十分实用;