Can’t use GPU for training or testing

dog-qiuqiu / Yolo-Fastest

:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+

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I used CUDA 10.2，cudnn 7.6.5，GPU NVIDIA GeForce RTX 2060

I have set up in Makefile GPU=1 CUDNN=1 ifeq ($(GPU), 1) COMMON+= -DGPU -I/usr/local/cuda-10.2/include/ CFLAGS+= -DGPU LDFLAGS+= -L/usr/local/cuda-10.2/lib64 -lcuda -lcudart -lcublas -lcurand

C:\Yolo-Fastest\build\darknet\x64> ./darknet.exe detector test ./cfg/voc.data ./cfg/yolo-fastest.cfg ./cfg/yolo-fastest.weights ./data/person.jpg -i 1 -thresh 0.25 -out_filename ./data/person_output.jpg

CUDA status Error: file: c:\yolo-fastest\src\dark_cuda.c : cuda_set_device() : line: 39 : build time: Nov 24 2020 - 18:36:35 CUDA Error: invalid device ordinal

Can anyone help to fix this?

dog-qiuqiu / Yolo-Fastest

Can’t use GPU for training or testing #35