yolo34py + AlexeyAB的坑¶
yolo原作者pjreddie不再更新了，yolo v4 是AlexeyAB的fork出品。
曾經用yolo34py API+ official libdarknet.so，但把darknet轉成AlexeyAB版本後會出錯，貌似用AlexeyAB的darknet.py也會出錯。
原因是free_network 的API不同。
解決辨法可以參考https://github.com/AlexeyAB/darknet/issues/3467
2 approachs:
- modify free_network, compile new so -> the darknet binary might be broken 我改了原用的free_network成_free_network, 然後加free_network給yolo34py用
- add api_free_network and change API(darknet.py or yolo34py) -> not compatible with pjreddie
object/pointer construction也跟official不同，比較難兼容…今後如果要用yolov4，大概直接拋棄pjreddie和yolo34py了
YOLOv4 vs CenterNet¶
The CenterNet used in Yolo v4 is NOT CenterNet: Objects as Points, which is the base of TTFNet.
darknet implement CenterNet: Triplet
So..currently there is not comparison between TTFNet/ CenterNet vs YOLOv4
Looking for TTFNet implement to darknet TTFnet: 10x Training Time Reduction · Issue #4690 · AlexeyAB/darknet
Makefile¶
| Description | |||
|---|---|---|---|
| GPU | build with CUDA to accelerate by using GPU (CUDA should be in /usr/local/cuda) | ||
| CUDNN | to build with cuDNN v5-v7 to accelerate training by using GPU (cuDNN should be in /usr/local/cudnn) | ||
| CUDNN_HALF | to build for mixed precision with Tensor Cores, speedup Detection 3x, Training 2x | ||
| OPENCV | build with OpenCV 4.x/3.x/2.4.x - allows to detect on video files and video streams from network cameras or web-cams | ||
| AVX | speed up CPU with Advanced Vector Extensions (check support via cat /proc/cpuinfo \| grep avx) |
||
| OPENMP | build with OpenMP support to accelerate Yolo by using multi-core CPU | ||
| LIBSO | build a library darknet.so and binary runable file uselib that uses this library | ||
| ZED_CAMERA, ZED_CAMERA_v2_8 | build a library with ZED-3D-camera support (should be ZED SDK installed) | ||
| USE_CPP | the ability to compile in C++ | ||
| DEBUG | build debug version of Yolo | ||
| ARCH | compute_XX refers to a PTX version. The arch= clause of the -gencode= command-line option to nvcc specifies the front-end compilation target and must always be a PTX version |
For my RTX 2070, using so lib for Python or C++ program:
GPU=1
CUDNN=1
CUDNN_HALF=1
OPENCV=1
AVX=0
OPENMP=0
LIBSO=1
ZED_CAMERA=0 # ZED SDK 3.0 and above
ZED_CAMERA_v2_8=0 # ZED SDK 2.X
USE_CPP=0
DEBUG=0
ARCH= -gencode arch=compute_75,code=[sm_75,compute_75]