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Added GPU selection feature to python inference #321

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merged 3 commits into from
May 24, 2022
Merged

Added GPU selection feature to python inference #321

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c3a7a04
Added GPU selection feature to python inference
cobanov May 6, 2022
6932819
pylint pep8 fixes
cobanov May 9, 2022
f1f7ca3
pep8 fixes
cobanov May 10, 2022
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6 changes: 5 additions & 1 deletion inference_realesrgan.py
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,9 @@ def main():
type=str,
default='auto',
help='Image extension. Options: auto | jpg | png, auto means using the same extension as inputs')
parser.add_argument(
'-g', '--gpu-id', type=int, default=None, help='gpu device to use (default=None) can be 0,1,2 for multi-gpu')

args = parser.parse_args()

# determine models according to model names
Expand Down Expand Up @@ -71,7 +74,8 @@ def main():
tile=args.tile,
tile_pad=args.tile_pad,
pre_pad=args.pre_pad,
half=not args.fp32)
half=not args.fp32,
gpu_id=args.gpu_id)

if args.face_enhance: # Use GFPGAN for face enhancement
from gfpgan import GFPGANer
Expand Down
17 changes: 15 additions & 2 deletions realesrgan/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,7 +26,16 @@ class RealESRGANer():
half (float): Whether to use half precision during inference. Default: False.
"""

def __init__(self, scale, model_path, model=None, tile=0, tile_pad=10, pre_pad=10, half=False, device=None):
def __init__(self,
scale,
model_path,
model=None,
tile=0,
tile_pad=10,
pre_pad=10,
half=False,
device=None,
gpu_id=None):
self.scale = scale
self.tile_size = tile
self.tile_pad = tile_pad
Expand All @@ -35,7 +44,11 @@ def __init__(self, scale, model_path, model=None, tile=0, tile_pad=10, pre_pad=1
self.half = half

# initialize model
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
if gpu_id:
self.device = torch.device(
f'cuda:{gpu_id}' if torch.cuda.is_available() else 'cpu') if device is None else device
else:
self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
# if the model_path starts with https, it will first download models to the folder: realesrgan/weights
if model_path.startswith('https://'):
model_path = load_file_from_url(
Expand Down