Comments (2)
from dlib-models.
Thanks for the quick response, I've resolved the issue.
Yes DLIB_USE_CUDA
was defined.
I switched the face detection
to use the cnn version and that I can clearly see running properly on my gpu. So by proxy the age estimation
model must also be accelerated.
I can't say fully but I believe its was a combination of the execution of the res-10
being so fast and low poling rate of my monitoring software, combo'ed with the slower feeding rate from the HOG detector lead to my monitoring software reporting no activity.
Thanks again for your time and your work :)
from dlib-models.
Related Issues (20)
- Trained HOG detector, but variation(jitter and shake) in bounding box output result.
- Computer specs required when training HOT 2
- Need more tuning of mmod_face_detector.dat's parameters
- How to train gender model? HOT 7
- Any trained model for ID card shape detector? HOT 2
- Details regarding mmod_human_face_detector HOT 3
- body pose model? HOT 4
- How to use dnn_gender_classifier_v1.dat in Python? HOT 4
- dlib_face_recognition_resnet_model_v1.dat dataset HOT 1
- Verification rate of face recognition model HOT 1
- 98 face landmarks
- How to config shape_predictor_68_face_landmarks.dat to use GPU HOT 1
- Details about training dnn_age_predictor_v1.dat.bz2 HOT 5
- how to get dlib_face_live_detector_v1.dat
- Is it possible to convert shape_predictor_68_face_landmarks dlib model to an onnx model? HOT 1
- Decrease in recognition rate HOT 2
- I would like to introduce the facial recognition model I trained, which includes a large number of Asian faces. HOT 2
- can i use face_recognition_densenet_model_v1.dat for landmarks generation ?
- dlib fails to load the models HOT 1
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