Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-08-31 19:11:59 +02:00
parent e926afd02b
commit 0a725a4bad
1 changed files with 5 additions and 10 deletions
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13
detect.py
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@ -7,23 +7,18 @@ from utils.datasets import *
from utils.utils import *
def detect(save_txt=False,
save_images=True):
def detect(save_txt=False, save_images=True):
img_size = (320, 192) if ONNX_EXPORT else opt.img_size # (320, 192) or (416, 256) or (608, 352) for (height, width)
out = opt.output
img_size = opt.img_size
# Initialize
device = torch_utils.select_device(force_cpu=ONNX_EXPORT)
torch.backends.cudnn.benchmark = False # set False for reproducible results
torch.backends.cudnn.benchmark = False # set False to speed up variable image size inference
if os.path.exists(out):
shutil.rmtree(out) # delete output folder
os.makedirs(out) # make new output folder
# Initialize model
if ONNX_EXPORT:
s = (320, 192) # (320, 192) or (416, 256) or (608, 352) onnx model image size (height, width)
model = Darknet(opt.cfg, s)
else:
model = Darknet(opt.cfg, img_size)
# Load weights
@ -40,7 +35,7 @@ def detect(save_txt=False,
# Export mode
if ONNX_EXPORT:
img = torch.zeros((1, 3, s[0], s[1]))
img = torch.zeros((1, 3) + img_size) # (1, 3, 320, 192)
torch.onnx.export(model, img, 'weights/export.onnx', verbose=True)
return