windows7 64bit Gefore GTX 680MX GPU anaconda
Download the CUDA Toolkit 10.1 update 2 version from the following site (TensorFlow 2.1.0 is supported because of CUDA Toolkit 10.1) https://developer.nvidia.com/cuda-toolkit-archive
Do not select Visual Studio Intergration for installation
If the installation is successful, execute nvcc -V
and the following result will be displayed.
C:\Windows\System32>nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:12:52_Pacific_Daylight_Time_2019
Cuda compilation tools, release 10.1, V10.1.243
Select and download cuDNN for CUDA 10.1 from the following site (Requires NVIDIA account) https://developer.nvidia.com/cudnn
Unzip the zip file and Rename the cuda folder to cuda765 and Copy to the path "C: \ Program Files \ NVIDIA GPU Computing Toolkit \ CUDA \ v10.1"
After copying
Add the following cuDNN path to PATH
C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1\cuda765\bin
conda create -n keras_work
activate keras_work
conda install tensorflow
(base) C:\Users\mac>activate keras_work
(keras_work) C:\Users\mac>python
Python 3.7.7 (default, Apr 15 2020, 05:09:04) [MSC v.1916 64 bit (AMD64)] :: Ana
conda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
2020-05-06 19:46:04.480481: I tensorflow/stream_executor/platform/default/dso_lo
ader.cc:44] Successfully opened dynamic library cudart64_101.dll
>>> print(tf.__version__)
2.1.0
>>> print(tf.test.is_gpu_available())
・ ・ ・
physical GPU (device: 0, name: GeForce GTX 680MX, pci bus id: 0000:01:00.0, compute capability: 3.0)
True
Get source from Github
cd c:\temp
git clone https://github.com/zzh8829/yolov3-tf2.git
cd yolov3-tf2
Download yolo3.weight from pjreddie.com
wget https://pjreddie.com/media/files/yolov3.weights --no-check-certificate
Since it is slow to get yolov3.weights from the above pjreddie.com, you can also download the following URL. https://pan.baidu.com/s/1G2Qh-V8kyLOq4oDbTwK6HQ Proposal (password): vogw The file is "yolo_tf2.1 \ data \ yolov3.weights"
Move yolo3.weight file to yolov3-tf2 path Confirm that the file has been moved
(keras_work) C:\temp\yolov3-tf2>dir /B *.weights
yolov3.weights
python convert.py --weights ./yolov3.weights --output ./checkpoints/yolov3.tf
python detect.py --image ./data/street.jpg
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