Comments (4)
Nice, I've seen that you open images directly from the path. You can get some inspiration from this example to make it work with PIL images or numpy arrays directly.
https://github.com/arrufat/wallyfinder
EDIT:
In particular, these two functions
https://github.com/arrufat/wallyfinder/blob/2a3ddc1af2b676ad434574fecd9be0004c0fcc23/src/wallyfinder.cpp#L8-L42
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@mowshon I'm really glad to see that the models I've released can find a usage... I am working on improving the model for enhancing gender detection for certain ethnic groups that are apparently under-represented in the original database.
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@davisking can you take a look at https://github.com/mowshon/age-and-gender
I don't have good skill in C++, but did my best for running this code on python.
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@arrufat wow! I realy need this! Thank you!
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Related Issues (20)
- How to reduce size of the model? HOT 1
- Would you be interested in a pretrainted ResNet50? HOT 3
- 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
- GPU Accerlation For Age Estimation HOT 2
- 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
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