Comments (10)
You need to have a custom-built OpenCV with Cuda enabled
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There's a bug right now that makes acceleration always appear as off. Just make sure you have the CUDA drivers installed and everything should work fine.
Acceleration is enabled but it just doesn't tell you -- I'm working on a bug fix for this.
from pine.
I still only get about 20fps though, is that expected from a 1050 Ti or should it be higher?
from pine.
I still only get about 20fps though, is that expected from a 1050 Ti or should it be higher?
@ixayy should be higher I get about 150 using a 1060
Sent with GitHawk
from pine.
I still only get about 20fps though, is that expected from a 1050 Ti or should it be higher?
@ixayy should be higher I get about 150 using a 1060
Sent with GitHawk
Could you possibly give me the instructions to properly get the acceleration working? I feel like I've done something wrong here.
from pine.
Make sure you installed cuda and cuDDN correctly.
If it still doesnt work, you could try to compile darknet and see if you get any errors
from pine.
Make sure you installed cuda and cuDDN correctly.
If it still doesnt work, you could try to compile darknet and see if you get any errors
I use it darknet with GTX 1070. I installed Cuda and CuDDN. Working.
I couldn't solve this problem.
from pine.
@AutisticDragon just install opencv-contrib-python or make own build with WITH_CUDA=ON ?
from pine.
980ti, going at about 30 fps, while CUDA seems OFF. Why is this? anybody can help?
from pine.
980ti, going at about 30 fps, while CUDA seems OFF. Why is this? anybody can help?
go to pine/lib/pine.py edit and search and then replace # load our YOLO object detector trained on COCO dataset (2 classes)
# and determine only the output layer names that we need from YOLO
print("[INFO] loading neural-network from disk...")
net = cv2.dnn.readNetFromDarknet(configPath, weightsPath)
net.setPreferableBackend(cv2.dnn.DNN_BACKEND_CUDA)
net.setPreferableTarget(cv2.dnn.DNN_TARGET_CUDA)
make sure both are cuda
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