Merge pull request #105 from Tencent/master

20200613

.travis.yml

@@ -71,7 +71,7 @@ matrix:
       dist: bionic
       env:
         - NAME=linux-gcc-arm32
-        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
+        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo rm /etc/apt/sources.list.d/mongodb*.list && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
         - BUILD="mkdir build && cd build && cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabihf.toolchain.cmake -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF - .. && make -j2 VERBOSE=1 && ctest --output-on-failure -j 2"
 
     - name: "linux-gcc-arm32-simplestl"
@@ -80,7 +80,7 @@ matrix:
       dist: bionic
       env:
         - NAME=linux-gcc-arm32-simplestl
-        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
+        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo rm /etc/apt/sources.list.d/mongodb*.list && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
         - BUILD="mkdir build && cd build && cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabihf.toolchain.cmake -DNCNN_SIMPLESTL=ON -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF - .. && make -j2 VERBOSE=1 && ctest --output-on-failure -j 2"
 
     - name: "test-coverage-arm32"
@@ -89,7 +89,7 @@ matrix:
       dist: bionic
       env:
         - NAME=linux-gcc-arm32
-        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
+        - BEFORE_BUILD="sudo dpkg --add-architecture armhf && sudo rm /etc/apt/sources.list.d/mongodb*.list && sudo apt-get update && sudo apt-get -y install crossbuild-essential-armhf libc6:armhf libstdc++-5-dev:armhf linux-libc-dev:armhf"
         - BUILD="mkdir build && cd build && cmake -DCMAKE_TOOLCHAIN_FILE=../toolchains/arm-linux-gnueabihf.toolchain.cmake -DCMAKE_BUILD_TYPE=debug -DNCNN_COVERAGE=ON -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF - .. && make -j2 && ctest --output-on-failure -j 2 && lcov -d ./src -c -o lcov.info && lcov -r lcov.info '/usr/*' -o lcov.info && lcov --list lcov.info && bash <(curl -s https://codecov.io/bash) -f lcov.info"
 
 before_install:

CMakeLists.txt

@@ -30,7 +30,7 @@ option(NCNN_PIXEL "convert and resize from/to image pixel" ON)
 option(NCNN_PIXEL_ROTATE "rotate image pixel orientation" ON)
 option(NCNN_CMAKE_VERBOSE "print verbose cmake messages" OFF)
 option(NCNN_VULKAN "vulkan compute support" OFF)
-option(NCNN_VULKAN_ONLINE_SPIRV "online SPIR-V module compilation" OFF)
+option(NCNN_VULKAN_ONLINE_SPIRV "online SPIR-V module compilation" ON)
 option(NCNN_REQUANT "auto merge int8 quant and dequant" OFF)
 option(NCNN_AVX2 "optimize x86 platform with avx2" OFF)
 option(NCNN_DISABLE_PIC "disable position-independent code" OFF)
@@ -65,7 +65,7 @@ if(NCNN_COVERAGE)
     set(CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} -coverage -lgcov")
 endif()
 
-if(NCNN_VULKAN_ONLINE_SPIRV)
+if(NCNN_VULKAN AND NCNN_VULKAN_ONLINE_SPIRV)
     if(NOT EXISTS "${CMAKE_CURRENT_SOURCE_DIR}/glslang/CMakeLists.txt")
         message(WARNING "The submodules were not downloaded! NCNN_VULKAN_ONLINE_SPIRV will be turned off.")
         message(WARNING "Please update submodules with \"git submodule update --init\" and try again.")

README.md

@@ -38,7 +38,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * Detection: MTCNN facedetection ...
 * Detection: VGG-SSD MobileNet-SSD SqueezeNet-SSD MobileNetV2-SSDLite ...
 * Detection: Faster-RCNN R-FCN ...
-* Detection: YOLOV2 YOLOV3 MobileNet-YOLOV3 ...
+* Detection: YOLOV2 YOLOV3 MobileNet-YOLOV3 YOLOV4...
 * Segmentation: FCN PSPNet UNet ...
 
 ---
@@ -96,7 +96,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * Supports multi-core parallel computing acceleration, ARM big.LITTLE cpu scheduling optimization
 * Supports GPU acceleration via the next-generation low-overhead vulkan api
 * The overall library size is less than 700K, and can be easily reduced to less than 300K
-* Extensible model design, supports 8bit quantization and half-precision floating point storage, can import caffe/pytorch/mxnet/onnx models
+* Extensible model design, supports 8bit quantization and half-precision floating point storage, can import caffe/pytorch/mxnet/onnx/darknet models
 * Support direct memory zero copy reference load network model
 * Can be registered with custom layer implementation and extended
 * Well, it is strong, not afraid of being stuffed with 卷   QvQ
@@ -111,7 +111,7 @@ ncnn 是一个为手机端极致优化的高性能神经网络前向计算框架
 * 支持多核并行计算加速，ARM big.LITTLE cpu 调度优化
 * 支持基于全新低消耗的 vulkan api GPU 加速
 * 整体库体积小于 700K，并可轻松精简到小于 300K
-* 可扩展的模型设计，支持 8bit 量化和半精度浮点存储，可导入 caffe/pytorch/mxnet/onnx 模型
+* 可扩展的模型设计，支持 8bit 量化和半精度浮点存储，可导入 caffe/pytorch/mxnet/onnx/darknet 模型
 * 支持直接内存零拷贝引用加载网络模型
 * 可注册自定义层实现并扩展
 * 恩，很强就是了，不怕被塞卷 QvQ