Open markpredigertrinamix opened 12 months ago
The Tasks library should do all pre-processing on your behalf. Have you tried just providing the original image?
Unfortunately we cannot use the mediapipe libraries due to very strict limitations of our embedded platform. We need to run the face landmarks model standalone and do the pre-/post-processing manually.
I had the same problem. I want to know, if I only have 256x256 face image, how should I do face landmarks detection. What pretreatment needs to be done? Or if there is any code that runs face_landmarks directly. Thanks a lot!
All of our pre-processing happens here: https://github.com/google/mediapipe/blob/8d57a9e2e815dd11a7434cb764382cc7ce4831a5/mediapipe/tasks/cc/components/processors/image_preprocessing_graph.cc#L67
You would have to look at how the specific tasks handles this graph.
Have I written custom code (as opposed to using a stock example script provided in MediaPipe)
None
OS Platform and Distribution
Embedded Linux
MediaPipe Tasks SDK version
No response
Task name (e.g. Image classification, Gesture recognition etc.)
Face landmarks
Programming Language and version (e.g. C++, Python, Java)
C++
Describe the actual behavior
Running the face landmarks model standalone on a cropped face patch
Describe the expected behaviour
Applying the correct preprocessing/normalization to the cropped face
Standalone code/steps you may have used to try to get what you need
Other info / Complete Logs
No response