Added wrappers/dlib/face example #4966
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
* BUILD_DLIB_EXAMPLES boolean in CMake to enable * Requires installing dlib separately and pointing to it with DLIB_DIR * wrappers/dlib/face example is listed in examples/readme.md * Fixed typo in rs-measure readme
dorodnic
approved these changes
Oct 23, 2019
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Tracked on: DSO-13630
This example demonstrates a very simple facial landmark detection using Dlib's machine learning algorithms, using depth data to implement basic anti-spoofing.
Faces detected by the camera will show landmarks in either green or red:
Green landmarks indicate a "real" face with depth data corroborating expectations. E.g., the distance to the eyes should be greater than to the tip of the nose, etc.
Red landmarks indicate a "fake" face. E.g., a picture of a face, where the distance to each facial feature does not meet expectations