Is it possible to use face_landmark.tflite from Mediapipe to generate face mesh in Android independently?

I'm working on a face tracking app (Android studio / Java) and I need to identify face landmarks. I'm interested using Mediapipe face mesh model. The problem is: I use Windows OS, and Mediapipe is not working on Windows OS.

I have very basic knowledge in Tensorflow, Can anybody explain to me how can i use Mediapipe's face_landmark.tflite model to detect faces in images and generate face mesh in Android studio with Java independently without the whole Mediapipe framework?

You can try look into my notebook below for usage example in python. This only needs tflite model and does not require Mediapipe installation.

https://nbviewer.jupyter.org/github/quickgrid/CodeLab/blob/master/tensorflow/MediaPipe_Face_Mesh_TFLite_Python_Direct_Inference.ipynb

This is the output image,

This should give a starting point to use android tflite interpreter to get face landmarks and draw them. It will require a face detector such as blazeface to output the face bounding box first.

As I have not implemented this model in android yet I cannot say what else may be needed. Further details may be found in mediapipe face mesh codes. The notebook is based on this code,

MediaPipe TensorflowLite Iris Model

https://github.com/shortcipher3/stackoverflow/blob/master/mediapipe_iris_2d_landmarks.ipynb

Further references,

https://github.com/google/mediapipe/blob/master/mediapipe/modules/face_landmark/face_landmark.tflite

https://google.github.io/mediapipe/solutions/face_mesh

Model card with input, output details,

https://drive.google.com/file/d/1QvwWNfFoweGVjsXF3DXzcrCnz-mx-Lha/view

Alternate option

Android ML Kit also has face landmarks with very good documentation and code example.

https://developers.google.com/ml-kit/vision/face-detection

https://developers.google.com/android/reference/com/google/mlkit/vision/face/package-summary