Comments (4)
Doc says: it can detect faces of dimension 48x48. Do the faces that you indicate have at least that size? Output also show a confidence called neighbours. You can use that according to your needs.
FYI. Model was trained on data from http://mmlab.ie.cuhk.edu.hk/projects/WIDERFace, caffe convolutional neural architecture is here: https://github.com/ShiqiYu/libfacedetection/tree/master/models/caffe
from image.
I saw that, and If you look at the URL in the code, the face is bigger than that. Just so it is clear, I am including a manually cut rectangle of 94 x 79 pixels, containing the face.
Tested with a photo with people with different ethnicities from Peru and it also failed. Might it be a training bias?
Will check the source materials for the model next weekend and report back if I get a hint of what's happening.
from image.
this face is 45x62 - why don't you take larger faces.
from image.
OK, you were correct. Sorry for that. High-res versions do work.
from image.
Related Issues (20)
- build notes
- Make wrapper around pretrained CNN https://github.com/ShiqiYu/libfacedetection
- implement densecrf
- Print output bounding boxes and labels from image_darknet_detect
- notes to myself
- Object recognition: apply *h5 cnn model to find an specific handwritten digit HOT 1
- [image.darknet] output error: file.exists(model) is not TRUE HOT 10
- Crash R session HOT 2
- CRAN issues HOT 2
- add DBoW2 HOT 2
- image_darknet_detect: "file" from memory object? HOT 1
- Extract lines from image_contour_detector HOT 7
- R crash when `union = T` in `image_line_segment_detector()` HOT 16
- how can I save the result of image_darknet_model into a R object? HOT 7
- installation error HOT 2
- namelist error on R HOT 4
- Session Crash HOT 9
- Line Segment Detector pixel matrix is 0 when union = T HOT 1
- image_surf only returns one non-zero dimension HOT 2
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