Comments (1)
Yup! The underlying models are all apache 2.0 licensed. https://storage.googleapis.com/mediapipe-assets/MediaPipe%20BlazeFace%20Model%20Card%20(Short%20Range).pdf
from mediapipe-samples.
Related Issues (20)
- Android LLM Inference Conversion guide for models fine tuned with keras nlp
- LLM Models other than Gemma , falcon, phi, stablelm HOT 1
- About face_detector performance issues in android HOT 3
- How to get LLM model performance? HOT 1
- Gemma-1.1-2B-it-cpu-int4.bin generating junk response in phone. HOT 5
- Gesture recognizer does not run on the emulator HOT 1
- LLM inference error when trying to run model locally, but works on Google's site HOT 1
- Native binaries are not compliant with Google Play 64-bit requirement HOT 1
- [Face Detection LandMark] Add a confidence score to the eye landmarks when wearing a black glasses
- Support for armeabi-v7a (32-bit ARM) the LLM Inference API
- The model is not a valid Flatbuffer buffer
- Unable to detect hand pose estimation for Android live app
- library "libllm_inference_engine_jni.so" not found - LLM inference for Android Example. HOT 1
- java.lang.ArrayIndexOutOfBoundsException occured when I run the android sample with model SSDMobileNet-V2
- Does this Android sample support features like NNAPI and NumThreads? HOT 3
- [Need Support]No example of object tracking were found
- There's isn't any code sample how to use Mediapipe Gesture Recognizer for Live Stream on Python using the Custom Model (.task) HOT 1
- ValueError: Mobile SSD models are expected to have exactly 4 outputs, found 2 HOT 1
- How to improve the performance of the object detection example in the Android sample?
- Face Stylizer example
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from mediapipe-samples.