M3D-VTON
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GPU Error when running the test examples
We are getting graphic card related error. Here are my system info
pavan@u-20:~/.../M3D-VTON$ sudo dmidecode -t 1
# dmidecode 3.2
Getting SMBIOS data from sysfs.
SMBIOS 3.0.0 present.
Handle 0x000C, DMI type 1, 27 bytes
System Information
Manufacturer: LENOVO
Product Name: 20JUS05X00
Version: ThinkPad L470 W10DG
Serial Number: PF11SM82
UUID: 31f6b94c-2fd0-11b2-a85c-ed0533b508ea
Wake-up Type: Power Switch
SKU Number: LENOVO_MT_20JU_BU_Think_FM_ThinkPad L470 W10DG
Family: ThinkPad L470 W10DG
pavan@u-20:~/.../M3D-VTON$
pavan@u-20:~/.../M3D-VTON$ inxi -G
Graphics: Device-1: Intel Skylake GT2 [HD Graphics 520] driver: i915 v: kernel
Display: x11 server: X.Org 1.20.13 driver: i915 resolution: 1366x768~60Hz
OpenGL: renderer: Mesa Intel HD Graphics 520 (SKL GT2) v: 4.6 Mesa 21.2.6
pavan@u-20:~/.../M3D-VTON$
pavan@u-20:~/.../M3D-VTON$ python3 test.py --model MTM --name MTM --dataroot mpv3d_example --datalist test_pairs --results_dir results
verbose: False
----------------- End -------------------
Traceback (most recent call last):
File "test.py", line 25, in <module>
opt = TestOptions().parse() # get test options
File "/home/pavan/Documents/aux/tmp-git/virtual-try-on/M3D-VTON/options/base_options.py", line 130, in parse
torch.cuda.set_device(opt.gpu_ids[0])
File "/home/pavan/.local/lib/python3.8/site-packages/torch/cuda/__init__.py", line 313, in set_device
torch._C._cuda_setDevice(device)
File "/home/pavan/.local/lib/python3.8/site-packages/torch/cuda/__init__.py", line 216, in _lazy_init
torch._C._cuda_init()
RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx
pavan@u-20:~/.../M3D-VTON$
is it possible to run it on my machine? I have attached my machine info also.
I have checked the information of ThinkPad L470 laptop and looks like it has no NVIDIA GPU support. Therefore it is nearly impossible to run M3D-VTON on this machine. A computer or server with NVIDIA GPU support is strongly preferred for running the code.