- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hello,
I'm quite new in the CNN world.
I'm satisfied with the face-detection-adas-0001 net's performance.
I now wonder what is the best way to detect if the detected faces are mostly frontal or of profile type.
The nets dedicated to the head pose seem to be unable to handle faces that are too much out-of-frontal. Is there a hope in checking the face-detection-adas-0001 layer activation, looking for some "profile face specialized locations" ?
If so, is there a way to convert back the .bin and .xml files to a framework (e.g. tensorflow, keras, caffe?) more suitable for "fine tuning" operations ?
Should I better go towards a frontal/profile classifier?
Best Regards ,
Erwan B.
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi Erwan,
I would suggest looking into the OpenVINO training extensions to achieve this https://github.com/opencv/openvino_training_extensions
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hi Roy,
thanks you !
I'll have a look at it.
E.B.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hello again,
Despite having the prototxt file face-detection-adas-0001 there is no caffemodel file for this particular net (that is very efficient on 16/9 images...) So I can't figure out to go back towards a well suited training framework...
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Dear Bigorgne, Erwan,
Also look at https://github.com/opencv/training_toolbox_caffe . Face Detection is one of the models covered. Unfortunately there is no way to "go backwards" from a generated IR file, back to the original model.
Thanks,
Shubha
![](/skins/images/C4F7392A5C68ACA60290C9576F107044/responsive_peak/images/icon_anonymous_message.png)
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page