Init Zelda

core/preprocess/hwvideoframe/CMakeLists.txt

+cmake_minimum_required(VERSION 3.2)
+project(hw-frame-extract)
+# SET(CUDA_VERSION 10.1)
+
+#gcc version
+#GCC('gcc482')
+#CUDA("10.1")
+set(global_cflags_str "-g -pipe -W -Wall -fPIC")
+set(CMAKE_C_FLAGS ${global_cflags_str})
+
+#C++ flags.
+set(global_cxxflags_str "-g -pipe -W -Wall -fPIC -std=c++11")
+set(CMAKE_CXX_FLAGS ${global_cxxflags_str})
+
+add_subdirectory(cuda)
+add_subdirectory(pybind11)
+set (EXTRA_LIBS ${EXTRA_LIBS} gpu)
+
+message(${CMAKE_CURRENT_SOURCE_DIR})
+include_directories("${CMAKE_CURRENT_SOURCE_DIR}/include")
+include_directories("${CMAKE_CURRENT_SOURCE_DIR}/pybind11/include")
+include_directories("/opt/compiler/cuda-10.1/include")
+include_directories("/home/work/wubohao/baidu/third-party/python/include/python2.7")
+
+file(GLOB SOURCE_FILES src/*.cpp pybind11/*.cpp )
+
+link_directories("-L/opt/compiler/cuda-10.1/lib64 -lcudart -lnppidei_static -lnppial_static -lnpps_static -lnppc_static -lculibos")
+# link_directories("/home/work/wubohao/baidu/third-party/python/lib")
+
+#.so
+add_library(gpupreprocess SHARED ${SOURCE_FILES})
+target_link_libraries (gpupreprocess ${EXTRA_LIBS})

core/preprocess/hwvideoframe/README.md

+# hwvideoframe
+简要说明
+
+## 快速开始
+如何构建、安装、运行
+
+## 测试
+如何执行自动化测试
+
+## 如何贡献
+贡献patch流程、质量要求
+
+## 讨论
+百度Hi讨论群：XXXX

core/preprocess/hwvideoframe/cuda/CMakeLists.txt

+cmake_minimum_required(VERSION 3.2)
+project(gpu)
+FIND_PACKAGE(CUDA ${CUDA_VERSION} REQUIRED)
+SET(CUDA_TARGET_INCLUDE ${CUDA_TOOLKIT_ROOT_DIR}-${CUDA_VERSION}/targets/${CMAKE_HOST_SYSTEM_PROCESSOR}-${LOWER_SYSTEM_NAME}/include)
+
+file(GLOB_RECURSE CURRENT_HEADERS  *.h *.hpp *.cuh)
+file(GLOB CURRENT_SOURCES  *.cpp *.cu)
+file(GLOB CUDA_LIBS /opt/compiler/cuda-10.1/lib64/*.so)
+
+source_group("Include" FILES ${CURRENT_HEADERS}) 
+source_group("Source" FILES ${CURRENT_SOURCES}) 
+
+set(CMAKE_CUDA_FLAGS "-ccbin /opt/compiler/gcc-4.8.2/bin -Xcompiler -fPIC --std=c++11")
+set(CUDA_NVCC_FLAGS "-L/opt/compiler/gcc-4.8.2/bin -Xcompiler -fPIC --std=c++11")
+
+include_directories("/opt/compiler/cuda-10.1/include")
+
+#cuda_add_library(gpu SHARED ${CURRENT_HEADERS} ${CURRENT_SOURCES})
+cuda_add_library(gpu SHARED ${CURRENT_HEADERS} ${CURRENT_SOURCES})
+target_link_libraries(gpu ${CUDA_LIBS})
+
+# import libgpupreprocess as pp
\ No newline at end of file

core/preprocess/hwvideoframe/cuda/resize.cu

+#include "cuda_runtime.h"
+
+#define clip(x, a, b) x >= a ? (x < b ? x : b-1) : a;
+
+const int INTER_RESIZE_COEF_BITS = 11;
+const int INTER_RESIZE_COEF_SCALE = 1 << INTER_RESIZE_COEF_BITS;
+
+__global__ void resizeCudaKernel( const float* input,
+                                  float* output,
+                                  const int inputWidth,
+                                  const int inputHeight,
+                                  const int outputWidth,
+                                  const int outputHeight,
+                                  const int inputChannels)
+{
+    //2D Index of current thread
+    const int dx = blockIdx.x * blockDim.x + threadIdx.x;
+    const int dy = blockIdx.y * blockDim.y + threadIdx.y;
+
+    if((dx < outputWidth) && (dy < outputHeight))
+    {
+        if(inputChannels == 1) { // grayscale image
+            // TODO: support grayscale
+        } else if(inputChannels == 3) { // RGB image
+
+            double scale_x = (double) inputWidth / outputWidth;
+            double scale_y = (double) inputHeight / outputHeight;
+
+            int xmax = outputWidth;
+
+            float fx = (float)((dx + 0.5) * scale_x - 0.5);
+            int sx = floorf(fx);
+            fx = fx - sx;
+
+            int isx1 = sx;
+            if (isx1 < 0) {
+                fx = 0.0;
+                isx1 = 0;
+            }
+            if (isx1 >= (inputWidth - 1)) {
+                xmax = ::min( xmax, dx);
+                fx = 0;
+                isx1 = inputWidth - 1;
+            }
+
+            float2 cbufx;
+            cbufx.x = (1.f - fx);
+            cbufx.y = fx;
+
+            float fy = (float)((dy + 0.5) * scale_y - 0.5);
+            int sy = floorf(fy);
+            fy = fy - sy;
+
+            int isy1 = clip(sy + 0, 0, inputHeight);
+            int isy2 = clip(sy + 1, 0, inputHeight);
+
+            float2 cbufy;
+            cbufy.x = (1.f - fy);
+            cbufy.y = fy;
+
+            int isx2 = isx1 + 1;
+
+            float3 d0;
+
+            float3 s11 = make_float3(input[(isy1 * inputWidth + isx1) * inputChannels + 0] , input[(isy1 * inputWidth + isx1) * inputChannels + 1] , input[(isy1 * inputWidth + isx1) * inputChannels + 2]);
+            float3 s12 = make_float3(input[(isy1 * inputWidth + isx2) * inputChannels + 0] , input[(isy1 * inputWidth + isx2) * inputChannels + 1] , input[(isy1 * inputWidth + isx2) * inputChannels + 2]);
+            float3 s21 = make_float3(input[(isy2 * inputWidth + isx1) * inputChannels + 0] , input[(isy2 * inputWidth + isx1) * inputChannels + 1] , input[(isy2 * inputWidth + isx1) * inputChannels + 2]);
+            float3 s22 = make_float3(input[(isy2 * inputWidth + isx2) * inputChannels + 0] , input[(isy2 * inputWidth + isx2) * inputChannels + 1] , input[(isy2 * inputWidth + isx2) * inputChannels + 2]);
+
+            float h_rst00, h_rst01;
+            // B
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.x;
+                h_rst01 = s21.x;
+            }
+            else
+            {
+                h_rst00 = s11.x * cbufx.x + s12.x * cbufx.y;
+                h_rst01 = s21.x * cbufx.x + s22.x * cbufx.y;
+            }
+            d0.x = h_rst00 * cbufy.x + h_rst01 * cbufy.y;
+
+            // G
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.y;
+                h_rst01 = s21.y;
+            }
+            else
+            {
+                h_rst00 = s11.y * cbufx.x + s12.y * cbufx.y;
+                h_rst01 = s21.y * cbufx.x + s22.y * cbufx.y;
+            }
+            d0.y = h_rst00 * cbufy.x + h_rst01 * cbufy.y;
+            // R
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.z;
+                h_rst01 = s21.z;
+            }
+            else
+            {
+                h_rst00 = s11.z * cbufx.x + s12.z * cbufx.y;
+                h_rst01 = s21.z * cbufx.x + s22.z * cbufx.y;
+            }
+            d0.z = h_rst00 * cbufy.x + h_rst01 * cbufy.y;
+
+            output[(dy*outputWidth + dx) * 3 + 0 ] = (d0.x); // R
+            output[(dy*outputWidth + dx) * 3 + 1 ] = (d0.y); // G
+            output[(dy*outputWidth + dx) * 3 + 2 ] = (d0.z); // B
+        } else {
+            // TODO: support alpha channel
+        }
+    }
+}
+
+__global__ void resizeCudaKernel_fixpt( const float* input,
+                                  float* output,
+                                  const int inputWidth,
+                                  const int inputHeight,
+                                  const int outputWidth,
+                                  const int outputHeight,
+                                  const int inputChannels)
+{
+    //2D Index of current thread
+    const int dx = blockIdx.x * blockDim.x + threadIdx.x;
+    const int dy = blockIdx.y * blockDim.y + threadIdx.y;
+
+    if((dx < outputWidth) && (dy < outputHeight))
+    {
+        if(inputChannels == 1) { // grayscale image
+            // TODO: support grayscale
+        } else if(inputChannels == 3) { // RGB image
+
+            double scale_x = (double) inputWidth / outputWidth;
+            double scale_y = (double) inputHeight / outputHeight;
+
+            int xmax = outputWidth;
+
+            float fx = (float)((dx + 0.5) * scale_x - 0.5);
+            int sx = floorf(fx);
+            fx = fx - sx;
+
+            int isx1 = sx;
+            if (isx1 < 0) {
+                fx = 0.0;
+                isx1 = 0;
+            }
+            if (isx1 >= (inputWidth - 1)) {
+                xmax = ::min( xmax, dx);
+                fx = 0;
+                isx1 = inputWidth - 1;
+            }
+
+            short2 cbufx;
+            cbufx.x = lrintf((1.f - fx) * INTER_RESIZE_COEF_SCALE);
+            cbufx.y = lrintf(fx * INTER_RESIZE_COEF_SCALE);
+
+            float fy = (float)((dy + 0.5) * scale_y - 0.5);
+            int sy = floorf(fy);
+            fy = fy - sy;
+
+            int isy1 = clip(sy + 0, 0, inputHeight);
+            int isy2 = clip(sy + 1, 0, inputHeight);
+
+            short2 cbufy;
+            cbufy.x = lrintf((1.f - fy) * INTER_RESIZE_COEF_SCALE);
+            cbufy.y = lrintf(fy * INTER_RESIZE_COEF_SCALE);
+
+            int isx2 = isx1 + 1;
+
+            uchar3 d0;
+
+            int3 s11 = make_int3(input[(isy1 * inputWidth + isx1) * inputChannels + 0] , input[(isy1 * inputWidth + isx1) * inputChannels + 1] , input[(isy1 * inputWidth + isx1) * inputChannels + 2]);
+            int3 s12 = make_int3(input[(isy1 * inputWidth + isx2) * inputChannels + 0] , input[(isy1 * inputWidth + isx2) * inputChannels + 1] , input[(isy1 * inputWidth + isx2) * inputChannels + 2]);
+            int3 s21 = make_int3(input[(isy2 * inputWidth + isx1) * inputChannels + 0] , input[(isy2 * inputWidth + isx1) * inputChannels + 1] , input[(isy2 * inputWidth + isx1) * inputChannels + 2]);
+            int3 s22 = make_int3(input[(isy2 * inputWidth + isx2) * inputChannels + 0] , input[(isy2 * inputWidth + isx2) * inputChannels + 1] , input[(isy2 * inputWidth + isx2) * inputChannels + 2]);
+
+            int h_rst00, h_rst01;
+            // B
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.x * INTER_RESIZE_COEF_SCALE;
+                h_rst01 = s21.x * INTER_RESIZE_COEF_SCALE;
+            }
+            else
+            {
+                h_rst00 = s11.x * cbufx.x + s12.x * cbufx.y;
+                h_rst01 = s21.x * cbufx.x + s22.x * cbufx.y;
+            }
+            d0.x = (unsigned char)(( ((cbufy.x * (h_rst00 >> 4)) >> 16) + ((cbufy.y * (h_rst01 >> 4)) >> 16) + 2) >> 2);
+
+            // G
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.y * INTER_RESIZE_COEF_SCALE;
+                h_rst01 = s21.y * INTER_RESIZE_COEF_SCALE;
+            }
+            else
+            {
+                h_rst00 = s11.y * cbufx.x + s12.y * cbufx.y;
+                h_rst01 = s21.y * cbufx.x + s22.y * cbufx.y;
+            }
+            d0.y = (unsigned char)(( ((cbufy.x * (h_rst00 >> 4)) >> 16) + ((cbufy.y * (h_rst01 >> 4)) >> 16) + 2) >> 2);
+            // R
+            if( dx > xmax - 1)
+            {
+                h_rst00 = s11.z * INTER_RESIZE_COEF_SCALE;
+                h_rst01 = s21.z * INTER_RESIZE_COEF_SCALE;
+            }
+            else
+            {
+                h_rst00 = s11.z * cbufx.x + s12.z * cbufx.y;
+                h_rst01 = s21.z * cbufx.x + s22.z * cbufx.y;
+            }
+            d0.z = (unsigned char)(( ((cbufy.x * (h_rst00 >> 4)) >> 16) + ((cbufy.y * (h_rst01 >> 4)) >> 16) + 2) >> 2);
+
+            output[(dy*outputWidth + dx) * 3 + 0 ] = (d0.x); // R
+            output[(dy*outputWidth + dx) * 3 + 1 ] = (d0.y); // G
+            output[(dy*outputWidth + dx) * 3 + 2 ] = (d0.z); // B
+        } else {
+            // TODO: support alpha channel
+        }
+    }
+}
+
+extern "C" cudaError_t resize_linear( const float* input,
+                                      float* output,
+                                      const int inputWidth,
+                                      const int inputHeight,
+                                      const int outputWidth,
+                                      const int outputHeight,
+                                      const int inputChannels,
+                                      const bool use_fixed_point) {
+    //Specify a reasonable block size
+    const dim3 block(16,16);
+
+    //Calculate grid size to cover the whole image
+    const dim3 grid((outputWidth + block.x - 1) / block.x, (outputHeight + block.y - 1) / block.y);
+
+    //Launch the size conversion kernel
+    if (use_fixed_point) {
+        resizeCudaKernel_fixpt<<<grid,block>>>(input, output, inputWidth, inputHeight, outputWidth, outputHeight, inputChannels);
+    } else {
+        resizeCudaKernel<<<grid,block>>>(input, output, inputWidth, inputHeight, outputWidth, outputHeight, inputChannels);
+    }
+
+    //Synchronize to check for any kernel launch errors
+    return cudaDeviceSynchronize();
+}
\ No newline at end of file

core/preprocess/hwvideoframe/include/center_crop.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file center_crop.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-15
+ **/
+
+#ifndef BAIDU_CVPRE_CENTER_CROP_H
+#define BAIDU_CVPRE_CENTER_CROP_H
+
+#include <memory>
+#include <npp.h>
+#include "op_context.h"
+
+// Crops the given Image at the center.
+// the size must not bigger than any inputs' height and width
+class CenterCrop {
+public:
+    CenterCrop(int size) : _size(size) {};
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    int _size;
+};
+
+#endif // BAIDU_CVPRE_CENTER_CROP_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/div.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file div.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-11
+ **/
+
+#ifndef BAIDU_CVPRE_DIV_H
+#define BAIDU_CVPRE_DIV_H
+
+#include <memory>
+#include <npp.h>
+#include "op_context.h"
+
+// divide by some float number for all pixel
+class Div {
+public:
+    Div(float value);
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    Npp32f _divisor;
+};
+
+#endif // BAIDU_CVPRE_DIV_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/image_io.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file image_io.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-08
+ **/
+
+#ifndef BAIDU_CVPRE_IMAGE_IO_H
+#define BAIDU_CVPRE_IMAGE_IO_H
+
+#include <memory>
+#include <npp.h>
+#include <pybind11/numpy.h>
+
+#include "op_context.h"
+
+// Input operator that copy numpy data to gpu buffer
+class Image2Gpubuffer {
+public:
+    std::shared_ptr<OpContext> operator()(pybind11::array_t<float> array);
+};
+
+// Output operator that copy gpu buffer data to numpy
+class Gpubuffer2Image {
+public:
+    pybind11::array_t<float> operator()(std::shared_ptr<OpContext> input);
+};
+
+#endif // BAIDU_CVPRE_IMAGE_IO_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/normalize.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file normalize.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-04
+ **/
+
+#ifndef BAIDU_CVPRE_NORMALIZE_H
+#define BAIDU_CVPRE_NORMALIZE_H
+
+#include <memory>
+#include <vector>
+#include <npp.h>
+#include "op_context.h"
+
+// utilize normalize operator on gpu
+class Normalize {
+public:
+    Normalize(const std::vector<float> &mean, const std::vector<float> &std, bool channel_first = false);
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    Npp32f _mean[CHANNEL_SIZE];
+    Npp32f _std[CHANNEL_SIZE]; 
+    bool _channel_first;            // indicate whether the channel is dimension 0, unsupported
+};
+
+#endif // BAIDU_CVPRE_NORMALIZE_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/op_context.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file op_context.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-03
+ **/
+
+#ifndef BAIDU_CVPRE_OPCONTEXT_H
+#define BAIDU_CVPRE_OPCONTEXT_H
+
+#include <npp.h>
+
+const size_t CHANNEL_SIZE = 3;
+
+// The context as input/ouput of all operators
+// contains pointer to raw data on gpu, frame size
+class OpContext {
+public:
+    OpContext() {
+        _step = 0;
+        _size = 0;
+        _p_frame = nullptr;
+    }
+    // constructor to apply gpu memory of image raw data
+    OpContext(int height, int width) {
+        _step = sizeof(Npp32f) * width * CHANNEL_SIZE;
+        _length = height * width * CHANNEL_SIZE;
+        _size = _step * height;
+        _nppi_size.height = height;
+        _nppi_size.width = width;
+        cudaMalloc((void **)(&_p_frame), _size);
+    }
+    virtual ~OpContext() {
+        free_memory();
+    }
+
+public:
+    Npp32f* p_frame() const {
+        return _p_frame;
+    }
+    int step() const {
+        return _step;
+    }
+    int length() const {
+        return _length;
+    }
+    int size() const {
+        return _size;
+    }
+    NppiSize& nppi_size() {
+        return _nppi_size;
+    }
+    void free_memory() {
+        if (_p_frame != nullptr) {
+            cudaFree(_p_frame);
+            _p_frame = nullptr;
+        }
+        _nppi_size.height = 0;
+        _nppi_size.width = 0;
+        _step = 0;
+        _size = 0;
+    }
+
+private:
+    Npp32f *_p_frame;       // pointer to raw data on gpu
+    int _step;              // number of bytes in a row
+    int _length;            // length of _p_frame, _size = _length * sizeof(Npp32f)
+    int _size;              // number of bytes of the image
+    NppiSize _nppi_size;    // contains height and width
+};
+
+#endif // BAIDU_CVPRE_OPCONTEXT_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/resize.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file resize.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-15
+ **/
+
+#ifndef BAIDU_CVPRE_RESIZE_H
+#define BAIDU_CVPRE_RESIZE_H
+
+#include <memory>
+#include <vector>
+
+#include <npp.h>
+#include "op_context.h"
+
+extern "C" cudaError_t resize_linear(const float* input,
+                                     float* output,
+                                     const int inputWidth,
+                                     const int inputHeight,
+                                     const int outputWidth,
+                                     const int outputHeight,
+                                     const int inputChannels,
+                                     const bool use_fixed_point);
+
+// Resize the input numpy array Image to the given size.
+// only support linear interpolation
+// only support RGB channels
+class Resize {
+public:
+    // size is an int, smaller edge of the image will be matched to this number.
+    Resize(int size, int max_size = 214748364, bool use_fixed_point = false, int interpolation = 0)
+            : _size(size), _max_size(max_size), _use_fixed_point(use_fixed_point), _interpolation(interpolation) {};
+    // size is a sequence like (w, h), output size will be matched to this
+    Resize(std::vector<int> size, int max_size = 214748364, bool use_fixed_point = false, int interpolation = 0)
+            : _size(-1), _max_size(max_size), _use_fixed_point(use_fixed_point), _interpolation(interpolation) {
+        _target_size[0] = size[0];
+        _target_size[1] = size[1];
+    }
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    int _size;              // target of smaller edge
+    int _target_size[2];    // target size sequence (w, h)
+    int _max_size;
+    bool _use_fixed_point;
+    int _interpolation;     // unused
+};
+
+#endif // BAIDU_CVPRE_RESIZE_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/resize_by_factor.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file resize_by_factor.h
+ * @author wubohao@baidu.com
+ * @date 2020-07-21
+ **/
+
+#ifndef BAIDU_CVPRE_RESIZE_BY_FACTOR_H
+#define BAIDU_CVPRE_RESIZE_BY_FACTOR_H
+
+#include <memory>
+#include <vector>
+
+#include <npp.h>
+#include "op_context.h"
+
+extern "C" cudaError_t resize_linear(const float *input,
+                                     float *output,
+                                     const int inputWidth,
+                                     const int inputHeight,
+                                     const int outputWidth,
+                                     const int outputHeight,
+                                     const int inputChannels,
+                                     const bool use_fixed_point);
+
+// Resize the input numpy array Image to a size multiple of factor which is usually required by a network
+// only support linear interpolation
+// only support RGB channels
+class ResizeByFactor
+{
+public:
+    // Resize factor. make width and height multiple factor of the value of factor. Default is 32
+    ResizeByFactor(int factor = 32, int max_side_len = 2400, bool use_fixed_point = false, int interpolation = 0)
+        : _factor(factor), _max_side_len(max_side_len), _use_fixed_point(use_fixed_point), _interpolation(interpolation){};
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    int _factor; // target of smaller edge
+    int _max_side_len;
+    bool _use_fixed_point;
+    int _interpolation; // unused
+};
+
+#endif // BAIDU_CVPRE_RESIZE_BY_FACTOR_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/rgb_swap.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file rgb_swap.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-01
+ **/
+
+#ifndef BAIDU_CVPRE_RGB_SWAP_H
+#define BAIDU_CVPRE_RGB_SWAP_H
+
+#include <memory>
+#include <npp.h>
+#include "op_context.h"
+
+// swap channel 0 and channel 2 for every pixel
+// both RGB2BGR and BGR2RGB use this operator
+class SwapChannel {
+public:
+    SwapChannel(){};
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    static const int _ORDER[CHANNEL_SIZE];  // describing how channel values are permutated
+};
+
+class RGB2BGR : public SwapChannel {};
+class BGR2RGB : public SwapChannel {};
+
+#endif // BAIDU_CVPRE_RGB_SWAP_H

core/preprocess/hwvideoframe/include/sub.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file sub.h
+ * @author yinyijun@baidu.com
+ * @date 2020-07-06
+ **/
+
+#ifndef BAIDU_CVPRE_SUB_H
+#define BAIDU_CVPRE_SUB_H
+
+#include <memory>
+#include <vector>
+#include <npp.h>
+#include "op_context.h"
+
+// subtract by some float numbers
+class Sub {
+public:
+    Sub(float subtractor);
+    Sub(const std::vector<float> &subtractors);
+    std::shared_ptr<OpContext> operator()(std::shared_ptr<OpContext> input);
+
+private:
+    Npp32f _subtractors[CHANNEL_SIZE];
+};
+
+#endif // BAIDU_CVPRE_SUB_H
\ No newline at end of file

core/preprocess/hwvideoframe/include/utils.h

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file rgb_swap.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-10
+ **/
+
+#ifndef BAIDU_CVPRE_UTILS_H
+#define BAIDU_CVPRE_UTILS_H
+
+#include <string>
+
+#include <npp.h>
+
+// verify return value of npp function
+// throw an exception if failed
+void verify_npp_ret(const std::string& function_name, NppStatus ret);
+
+// verify return value of cuda runtime function
+// throw an exception if failed
+void verify_cuda_ret(const std::string& function_name, cudaError_t ret);
+
+#endif // BAIDU_CVPRE_UTILS_H
\ No newline at end of file

core/preprocess/hwvideoframe/pybind/pybind_gpu_preprocess.cpp

+#include <pybind11/pybind11.h>
+#include <pybind11/stl.h>
+
+#include "div.h"
+#include "sub.h"
+#include "image_io.h"
+#include "rgb_swap.h"
+#include "normalize.h"
+#include "center_crop.h"
+#include "resize.h"
+#include "resize_by_factor.h"
+
+PYBIND11_MODULE(libgpupreprocess, m) {
+    pybind11::class_<OpContext, std::shared_ptr<OpContext>>(m, "OpContext");
+    pybind11::class_<Image2Gpubuffer>(m, "Image2Gpubuffer")
+        .def(pybind11::init<>())
+        .def("__call__", &Image2Gpubuffer::operator());
+    pybind11::class_<Gpubuffer2Image>(m, "Gpubuffer2Image")
+        .def(pybind11::init<>())
+        .def("__call__", &Gpubuffer2Image::operator());
+    pybind11::class_<RGB2BGR>(m, "RGB2BGR")
+        .def(pybind11::init<>())
+        .def("__call__", &RGB2BGR::operator());
+    pybind11::class_<BGR2RGB>(m, "BGR2RGB")
+        .def(pybind11::init<>())
+        .def("__call__", &BGR2RGB::operator());
+    pybind11::class_<Div>(m, "Div")
+        .def(pybind11::init<float>())
+        .def("__call__", &Div::operator());
+    pybind11::class_<Sub>(m, "Sub")
+        .def(pybind11::init<float>())
+        .def(pybind11::init<const std::vector<float>&>())
+        .def("__call__", &Sub::operator());
+    pybind11::class_<Normalize>(m, "Normalize")
+        .def(pybind11::init<const std::vector<float>&, const std::vector<float>&, bool>(),
+            pybind11::arg("mean"), pybind11::arg("std"), pybind11::arg("channel_first") = false)
+        .def("__call__", &Normalize::operator());
+    pybind11::class_<CenterCrop>(m, "CenterCrop")
+        .def(pybind11::init<int>())
+        .def("__call__", &CenterCrop::operator());
+    pybind11::class_<Resize>(m, "Resize")
+        .def(pybind11::init<int, int, bool>(),
+            pybind11::arg("size"),
+            pybind11::arg("max_size") = 214748364,
+            pybind11::arg("use_fixed_point") = false)
+        .def(pybind11::init<const std::vector<int>&, int, bool>(),
+            pybind11::arg("target_size"),
+            pybind11::arg("max_size") = 214748364,
+            pybind11::arg("use_fixed_point") = false)
+        .def("__call__", &Resize::operator());
+    pybind11::class_<ResizeByFactor>(m, "ResizeByFactor")
+        .def(pybind11::init<int, int, bool>(),
+            pybind11::arg("factor") = 32,
+            pybind11::arg("max_side_len") = 2400,
+            pybind11::arg("use_fixed_point") = false)
+        .def("__call__", &ResizeByFactor::operator());
+}
+

core/preprocess/hwvideoframe/src/center_crop.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file center_crop.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-15
+ **/
+#include "center_crop.h"
+
+#include <algorithm>
+
+#include <npp.h>
+#include "utils.h"
+
+std::shared_ptr<OpContext> CenterCrop::operator()(std::shared_ptr<OpContext> input) {
+    int new_width = std::min(_size, input->nppi_size().width);
+    int new_height = std::min(_size, input->nppi_size().height);
+    auto output = std::make_shared<OpContext>(new_height, new_width);
+    int x_start = (input->nppi_size().width - new_width) / 2;
+    int y_start = (input->nppi_size().height - new_height) / 2;
+    Npp32f* p_src = input->p_frame()
+                    + y_start * input->nppi_size().width * CHANNEL_SIZE
+                    + x_start * CHANNEL_SIZE;
+    NppStatus ret = nppiCopy_32f_C3R(p_src,
+                                     input->step(),
+                                     output->p_frame(),
+                                     output->step(),
+                                     output->nppi_size());
+    verify_npp_ret("nppiCopy_32f_C3R", ret);
+    return output;
+}

core/preprocess/hwvideoframe/src/div.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file div.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-11
+ **/
+#include "div.h"
+
+#include <stdexcept>
+
+#include <npp.h>
+#include "utils.h"
+
+Div::Div(float value) {
+    _divisor = value;
+}
+
+std::shared_ptr<OpContext> Div::operator()(std::shared_ptr<OpContext> input) {
+    NppStatus ret = nppsDivC_32f_I(_divisor, input->p_frame(), input->length());
+    verify_npp_ret("nppsDivC_32f_I", ret);
+    return input;
+}

core/preprocess/hwvideoframe/src/image_io.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file image_io.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-08
+ **/
+#include "image_io.h"
+
+#include <stdexcept>
+
+#include <cuda_runtime.h>
+#include <pybind11/numpy.h>
+#include "utils.h"
+
+std::shared_ptr<OpContext> Image2Gpubuffer::operator()(pybind11::array_t<float> input) {
+    pybind11::buffer_info buf = input.request();
+    if (buf.format != pybind11::format_descriptor<float>::format()) {
+        throw std::runtime_error("Incompatible format: expected a float numpy!");
+    }
+    if (buf.ndim != 3) {
+        throw std::runtime_error("Number of dimensions must be three");
+    }
+    if (buf.shape[2] != CHANNEL_SIZE) {
+        throw std::runtime_error("Number of channels must be three");
+    }
+    auto result = std::make_shared<OpContext>(buf.shape[0], buf.shape[1]);
+    auto ret = cudaMemcpy(result->p_frame(), static_cast<float*>(buf.ptr), result->size(), cudaMemcpyHostToDevice);
+    verify_cuda_ret("cudaMemcpy", ret);
+    return result;
+}
+
+pybind11::array_t<float> Gpubuffer2Image::operator()(std::shared_ptr<OpContext> input) {
+    auto result = pybind11::array_t<float>({ input->nppi_size().height, input->nppi_size().width, (int)CHANNEL_SIZE });
+    pybind11::buffer_info buf = result.request();
+    auto ret = cudaMemcpy(static_cast<float*>(buf.ptr), input->p_frame(), input->size(), cudaMemcpyDeviceToHost);
+    verify_cuda_ret("cudaMemcpy", ret);
+    return result;
+}

core/preprocess/hwvideoframe/src/normalize.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file normalize.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-04
+ **/
+#include "normalize.h"
+#include <stdexcept>
+
+#include <npp.h>
+#include "utils.h"
+
+Normalize::Normalize(const std::vector<float> &mean, const std::vector<float> &std, bool channel_first) {
+    if (mean.size() != CHANNEL_SIZE) {
+        throw std::runtime_error("size of mean must be three");
+    }
+    if (std.size() != CHANNEL_SIZE) {
+        throw std::runtime_error("size of std must be three");
+    }
+    for (size_t i = 0; i < CHANNEL_SIZE; i++) {
+        _mean[i] = mean[i];
+        _std[i] = std[i];
+    }
+    _channel_first = channel_first;
+}
+
+std::shared_ptr<OpContext> Normalize::operator()(std::shared_ptr<OpContext> input) {
+    NppStatus ret = nppiSubC_32f_C3IR(_mean, input->p_frame(), input->step(), input->nppi_size());
+    verify_npp_ret("nppiSubC_32f_C3IR", ret);
+    ret = nppiDivC_32f_C3IR(_std, input->p_frame(), input->step(), input->nppi_size());
+    verify_npp_ret("nppiDivC_32f_C3IR", ret);
+    return input;
+}

core/preprocess/hwvideoframe/src/resize.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file resize.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-15
+ **/
+#include "resize.h"
+
+#include <sstream>
+#include <math.h>
+
+#include "utils.h"
+
+std::shared_ptr<OpContext> Resize::operator()(std::shared_ptr<OpContext> input) {
+    int resized_width = 0, resized_height = 0;
+    if (_size == -1) {
+        resized_width = std::min(_target_size[0], _max_size);
+        resized_height = std::min(_target_size[1], _max_size);
+    } else {
+        int im_max_size = std::max(input->nppi_size().height, input->nppi_size().width);
+        float percent = (float)_size / std::min(input->nppi_size().height, input->nppi_size().width);
+        if (round(percent * im_max_size) > _max_size) {
+            percent = float(_max_size) / float(im_max_size);
+        }
+        resized_width = int(round(input->nppi_size().width * percent));
+        resized_height = int(round(input->nppi_size().height * percent));
+    }
+    auto output = std::make_shared<OpContext>(resized_height, resized_width);
+    auto ret = resize_linear(input->p_frame(),
+                               output->p_frame(),
+                               input->nppi_size().width,
+                               input->nppi_size().height,
+                               output->nppi_size().width,
+                               output->nppi_size().height,
+                               CHANNEL_SIZE,
+                               _use_fixed_point);
+    verify_cuda_ret("resize_linear", ret);
+    return output;
+}

core/preprocess/hwvideoframe/src/resize_by_factor.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file resize_by_factor.cpp
+ * @author wubohao@baidu.com
+ * @date 2020-07-21
+ **/
+#include "resize_by_factor.h"
+
+#include <sstream>
+#include <math.h>
+
+#include "resize.h"
+#include "utils.h"
+
+std::shared_ptr<OpContext> ResizeByFactor::operator()(std::shared_ptr<OpContext> input)
+{
+    int resized_width = input->nppi_size().width, resized_height = input->nppi_size().height;
+    float radio = 0;
+    if (std::max(resized_width, resized_height) > _max_side_len)
+    {
+        if (resized_width > resized_height)
+        {
+            radio = float(_max_side_len / resized_width);
+        }
+        else
+        {
+            radio = float(_max_side_len / resized_height);
+        }
+    }
+    else
+    {
+        radio = 1;
+    }
+    resized_width = int(resized_width * radio);
+    resized_height = int(resized_height * radio);
+    if (resized_height % _factor == 0)
+    {
+        resized_height = resized_height;
+    }
+    else if (floor(resized_height / _factor) <= 1)
+    {
+        resized_height = _factor;
+    }
+    else
+    {
+        resized_height = (floor(resized_height / 32) - 1) * 32;
+    }
+    if (resized_width % _factor == 0)
+    {
+        resized_width = resized_width;
+    }
+    else if (floor(resized_width / _factor) <= 1)
+    {
+        resized_width = _factor;
+    }
+    else
+    {
+        resized_width = (floor(resized_width / 32) - 1) * _factor;
+    }
+    if (int(resized_width) <= 0 || int(resized_height) <= 0)
+    {
+        return NULL;
+    }
+    auto output = std::make_shared<OpContext>(resized_height, resized_width);
+    auto ret = resize_linear(input->p_frame(),
+                             output->p_frame(),
+                             input->nppi_size().width,
+                             input->nppi_size().height,
+                             output->nppi_size().width,
+                             output->nppi_size().height,
+                             CHANNEL_SIZE,
+                             _use_fixed_point);
+    verify_cuda_ret("resize_linear", ret);
+    return output;
+}

core/preprocess/hwvideoframe/src/rgb_swap.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file ExtractFrameJpeg.h
+ * @author yinyijun@baidu.com
+ * @date 2020-06-01
+ **/
+#include "rgb_swap.h"
+
+#include <npp.h>
+#include "utils.h"
+
+const int SwapChannel::_ORDER[CHANNEL_SIZE] = {2, 1, 0};
+
+std::shared_ptr<OpContext> SwapChannel::operator()(std::shared_ptr<OpContext> input) {
+    NppStatus ret = nppiSwapChannels_32f_C3IR(input->p_frame(), input->step(), input->nppi_size(), _ORDER);
+    verify_npp_ret("nppiSwapChannels_32f_C3IR", ret);
+    return input;
+}

core/preprocess/hwvideoframe/src/sub.cpp

+/*******************************************
+ *
+ * Copyright (c) 2020 Baidu.com, Inc. All Rights Reserved
+ *
+ ******************************************/
+/**
+ * @file sub.cpp
+ * @author yinyijun@baidu.com
+ * @date 2020-06-11
+ **/
+#include "sub.h"
+
+#include <stdexcept>
+
+#include <npp.h>
+#include "utils.h"
+
+Sub::Sub(float subtractor) {
+    for (size_t i = 0; i < CHANNEL_SIZE; i++) {
+        _subtractors[i] = subtractor;
+    }
+}
+
+Sub::Sub(const std::vector<float> &subtractors) {
+    if (subtractors.size() != CHANNEL_SIZE) {
+        throw std::runtime_error("size of subtractors must be three");
+    }
+    for (size_t i = 0; i < CHANNEL_SIZE; i++) {
+        _subtractors[i] = subtractors[i];
+    }
+}
+
+std::shared_ptr<OpContext> Sub::operator()(std::shared_ptr<OpContext> input) {
+    NppStatus ret = nppiSubC_32f_C3IR(_subtractors, input->p_frame(), input->step(), input->nppi_size());
+    verify_npp_ret("nppiSubC_32f_C3IR", ret);
+    return input;
+}

core/preprocess/hwvideoframe/src/utlis.cpp

+
+#include <sstream>
+#include <stdexcept>
+
+#include <npp.h>
+
+#include "utils.h"
+
+void verify_npp_ret(const std::string& function_name, NppStatus ret) {
+    if (ret != NPP_SUCCESS) {
+        std::ostringstream ss;
+        ss << function_name << ", ret: " << ret;
+        throw std::runtime_error(ss.str());
+    }
+}
+
+void verify_cuda_ret(const std::string& function_name, cudaError_t ret) {
+    if (ret != cudaSuccess) {
+        std::ostringstream ss;
+        ss << function_name << ", ret: " << ret;
+        throw std::runtime_error(ss.str());
+    }
+}
\ No newline at end of file

python/paddle_serving_app/reader/test_audio_reader.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from audio_reader import AudioFeatureOp
+
+if __name__ == '__main__':
+    local_video_path = 'case.mp4'
+    test_op = AudioFeatureOp()
+    test_op.extract_audio_from_video(local_video_path)
\ No newline at end of file

python/paddle_serving_app/reader/test_frame_reader.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+hwextract lib use case
+"""
+import paddle_serving_app.reader.hwextract
+import sys
+if __name__ == '__main__':
+    handler = hwextract.HwExtractFrameJpeg(0)
+    # 0, gpu card index
+    # if you want BGRA Raw Data, plz use HwExtractBGRARaw
+    handler.init_handler()
+    # init once can decode many videos
+    video_file_name = sys.argv[1]
+    # for now just support h264 codec
+    frame_list = []
+    try:
+        frame_list = handler.extract_frame(video_file_name, 1)
+        # specifiy file name and fps you want to extract, 0 for all frame
+    except Exception as e_frame:
+        print("Failed to cutframe, exception[%s]" % (e_frame))
+        sys.exit(1)
+    for item in frame_list:
+        print "i am a item in frame_list"
+        # do something, for instance
+        # jpeg_array = np.array(item, copy=False)
+        # img = cv2.imdecode(item, cv2.IMREAD_COLOR)
+        # etc.....
+        item.free_memory()
+        # have to release memory
\ No newline at end of file

python/paddle_serving_app/reader/test_functional.py

+# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import sys
+import numpy as np
+from paddle_serving_app.reader import Sequential, Resize, File2Image
+import libgpupreprocess as pp
+
+
+class TestOperators(unittest.TestCase):
+    """
+    test all operators, e.g. Div, Normalize
+    """
+
+    def test_div(self):
+        """
+        test Div
+        """
+        height = 4
+        width = 5
+        channels = 3
+        value = 255.0
+        img = np.arange(height * width * channels).reshape(
+            [height, width, channels])
+        seq = Sequential(
+            [pp.Image2Gpubuffer(), pp.Div(value), pp.Gpubuffer2Image()])
+        result = seq(img).reshape(-1)
+        for i in range(0, result.size):
+            self.assertAlmostEqual(i / value, result[i], 5)
+
+    def test_sub(self):
+        """
+        test Sub
+        """
+        height = 4
+        width = 5
+        channels = 3
+        img = np.arange(height * width * channels).reshape(
+            [height, width, channels])
+
+        # input size is an int
+        value = 10.0
+        seq = Sequential(
+            [pp.Image2Gpubuffer(), pp.Sub(value), pp.Gpubuffer2Image()])
+        result = seq(img).reshape(-1)
+        for i in range(0, result.size):
+            self.assertEqual(i - value, result[i])
+
+        # input size is a sequence
+        values = (9, 4, 2)
+        seq = Sequential(
+            [pp.Image2Gpubuffer(), pp.Sub(values), pp.Gpubuffer2Image()])
+        result = seq(img)
+        for i in range(0, result.shape[0]):
+            for j in range(0, result.shape[1]):
+                for k in range(0, result.shape[2]):
+                    self.assertEqual(result[i][j][k], img[i][j][k] - values[k])
+
+    def test_normalize(self):
+        """
+        test Normalize
+        """
+        height = 4
+        width = 5
+        channels = 3
+        img = np.random.rand(height, width, channels)
+        mean = [5.0, 5.0, 5.0]
+        std = [2.0, 2.0, 2.0]
+        seq = Sequential([
+            pp.Image2Gpubuffer(), pp.Normalize(mean, std), pp.Gpubuffer2Image()
+        ])
+        result = seq(img)
+        for i in range(0, height):
+            for j in range(0, width):
+                for k in range(0, channels):
+                    self.assertAlmostEqual((img[i][j][k] - mean[k]) / std[k],
+                                           result[i][j][k], 5)
+
+    def test_center_crop(self):
+        """
+        test CenterCrop
+        """
+        height = 9
+        width = 7
+        channels = 3
+        img = np.arange(height * width * channels).reshape(
+            [height, width, channels])
+        new_size = 5
+        seq = Sequential([
+            pp.Image2Gpubuffer(), pp.CenterCrop(new_size), pp.Gpubuffer2Image()
+        ])
+        result = seq(img)
+        self.assertEqual(result.shape[0], new_size)
+        self.assertEqual(result.shape[1], new_size)
+        self.assertEqual(result.shape[2], channels)
+
+    def test_resize(self):
+        """
+        test Resize
+        """
+        height = 9
+        width = 5
+        channels = 3
+        img = np.arange(height * width).reshape([height, width, 1]) * np.ones(
+            (1, channels))
+
+        # input size is an int
+        for new_size in [3, 10]:
+            seq_gpu = Sequential([
+                pp.Image2Gpubuffer(), pp.Resize(new_size), pp.Gpubuffer2Image()
+            ])
+            seq_paddle = Sequential([Resize(new_size)])
+            result_gpu = seq_gpu(img)
+            result_paddle = seq_paddle(img)
+            self.assertEqual(result_gpu.shape, result_paddle.shape)
+            for i in range(0, result_gpu.shape[0]):
+                for j in range(0, result_gpu.shape[1]):
+                    for k in range(0, result_gpu.shape[2]):
+                        self.assertAlmostEqual(result_gpu[i][j][k],
+                                               result_paddle[i][j][k], 5)
+
+        # input size is a sequence
+        for new_height, new_width in [(7, 3), (15, 10)]:
+            seq_gpu = Sequential([
+                pp.Image2Gpubuffer(), pp.Resize((new_width, new_height)),
+                pp.Gpubuffer2Image()
+            ])
+            seq_paddle = Sequential([Resize((new_width, new_height))])
+            result_gpu = seq_gpu(img)
+            result_paddle = seq_paddle(img)
+            self.assertEqual(result_gpu.shape, result_paddle.shape)
+            for i in range(0, result_gpu.shape[0]):
+                for j in range(0, result_gpu.shape[1]):
+                    for k in range(0, result_gpu.shape[2]):
+                        self.assertAlmostEqual(result_gpu[i][j][k],
+                                               result_paddle[i][j][k], 5)
+
+    def test_resize_fixed_point(self):
+        """
+        test Resize by using fixed-point
+        """
+        new_height = 256
+        new_width = 256 * 4 / 3
+        seq = Sequential([
+            File2Image(), pp.Image2Gpubuffer(), pp.Resize(
+                (new_width, new_height), use_fixed_point=True),
+            pp.Gpubuffer2Image()
+        ])
+        img = seq("./capture_16.bmp")
+        img = np.resize(img, (new_height, new_width * 3))
+        img_vis = np.loadtxt("./cap_resize_16.raw")
+        img_resize_diff = img_vis - img
+        self.assertEqual(np.all(img_resize_diff == 0), True)
+
+
+if __name__ == '__main__':
+    unittest.main()
\ No newline at end of file

python/setup.py.app.in

@@ -16,6 +16,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
+import platform
 import os
 
 from setuptools import setup, Distribution, Extension
@@ -23,17 +24,33 @@ from setuptools import find_packages
 from setuptools import setup
 from paddle_serving_app.version import serving_app_version
 from pkg_resources import DistributionNotFound, get_distribution
-import util
         
-max_version, mid_version, min_version = util.python_version()
+def python_version():
+    return [int(v) for v in platform.python_version().split(".")]
+
+def find_package(pkgname):
+    try:
+        get_distribution(pkgname)
+        return True
+    except DistributionNotFound:
+        return False
+
+max_version, mid_version, min_version = python_version()
 
 if '${PACK}' == 'ON':
     copy_lib()
 
+os.system('cp ../core/preprocess/nvdec-extractframe/libhwextract.so ./')
+os.system('mv ./libhwextract.so ./paddle_serving_app/reader/hwextract.so')
+os.system('cp ../core/preprocess/hwvideoframe/libgpupreprocess.so ./paddle_serving_app/reader')
+os.system('mkdir ./paddle_serving_app/reader/lib')
+os.system('cp ../core/preprocess/nvdec-extractframe/cuda/libhwgpu.so ./paddle_serving_app/reader/lib')
+os.system('cp ../core/preprocess/hwvideoframe/cuda/libgpu.so ./paddle_serving_app/reader/lib')
+os.system('export LD_LIBRARY_PATH="./paddle_serving_app/reader/lib"')
 
 REQUIRED_PACKAGES = [
     'six >= 1.10.0', 'sentencepiece', 'opencv-python<=4.2.0.32', 'pillow',
-    'shapely<=1.6.1', 'pyclipper'
+    'shapely', 'pyclipper'
 ]
 
 packages=['paddle_serving_app',
@@ -41,9 +58,11 @@ packages=['paddle_serving_app',
           'paddle_serving_app.reader',
 	  'paddle_serving_app.utils',
 	  'paddle_serving_app.models',
-	  'paddle_serving_app.reader.pddet']
+	  'paddle_serving_app.reader.pddet',
+          'paddle_serving_app.reader.lib']
 
-package_data={}
+package_data={'paddle_serving_app': ['reader/*.so']}
+              # 'paddle_serving_app.reader': ['lib/*.so']}
 package_dir={'paddle_serving_app':
              '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_app',
 	     'paddle_serving_app.proto':
@@ -55,7 +74,9 @@ package_dir={'paddle_serving_app':
 	     'paddle_serving_app.models':
 	     '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_app/models',
 	     'paddle_serving_app.reader.pddet':
-	     '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_app/reader/pddet',}
+	     '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_app/reader/pddet',
+             'paddle_serving_app.reader.lib':
+             '${PADDLE_SERVING_BINARY_DIR}/python/paddle_serving_app/reader/lib',}
 
 setup(
     name='paddle-serving-app',
@@ -89,4 +110,4 @@ setup(
         'Topic :: Software Development :: Libraries :: Python Modules',
     ],
     license='Apache 2.0',
-    keywords=('paddle-serving serving-client deployment industrial easy-to-use'))
+    keywords=('paddle-serving serving-client deployment industrial easy-to-use'))
\ No newline at end of file