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author | Éanna Ó Catháin <eanna.ocathain@arm.com> | 2021-09-15 09:32:30 +0100 |
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committer | Kshitij Sisodia <kshitij.sisodia@arm.com> | 2021-09-16 16:01:23 +0100 |
commit | 8f9588721cbb7356b03a714c97d6b3a9a6e89438 (patch) | |
tree | 1ca19d31958081c09f360d91e15fefb6e38b3992 /docs/documentation.md | |
parent | e6588f620c648dd0492f6133152855d77c672568 (diff) | |
download | ml-embedded-evaluation-kit-8f9588721cbb7356b03a714c97d6b3a9a6e89438.tar.gz |
MLECO-2082: Adding visual wake word use case21.08
MLECO-2083: Refactoring img_class and visual wake word
*Added source files for visual wake word
*Added tests
*Added docs
*Added new images for visual wake word demo
*Refactored common functions in img_class, visual wake word and other usecases
Change-Id: Ibd25854e19a5517f940a8d3086a5d4835fab89e9
Signed-off-by: Éanna Ó Catháin <eanna.ocathain@arm.com>
Diffstat (limited to 'docs/documentation.md')
-rw-r--r-- | docs/documentation.md | 1 |
1 files changed, 1 insertions, 0 deletions
diff --git a/docs/documentation.md b/docs/documentation.md index 59c1650..28b9eda 100644 --- a/docs/documentation.md +++ b/docs/documentation.md @@ -210,6 +210,7 @@ The models used in the use-cases implemented in this project can be downloaded f - [DS-CNN](https://github.com/ARM-software/ML-zoo/tree/68b5fbc77ed28e67b2efc915997ea4477c1d9d5b//models/keyword_spotting/ds_cnn_large/tflite_clustered_int8). - [Wav2Letter](https://github.com/ARM-software/ML-zoo/tree/1a92aa08c0de49a7304e0a7f3f59df6f4fd33ac8/models/speech_recognition/wav2letter/tflite_pruned_int8). - [Anomaly Detection](https://github.com/ARM-software/ML-zoo/tree/7c32b097f7d94aae2cd0b98a8ed5a3ba81e66b18/models/anomaly_detection/micronet_medium/tflite_int8). +- [Visual Wake Word](https://github.com/ARM-software/ML-zoo/raw/7dd3b16bb84007daf88be8648983c07f3eb21140/models/visual_wake_words/micronet_vww4/tflite_int8/vww4_128_128_INT8.tflite). When using *Ethos-U* NPU backend, Vela compiler optimizes the the NN model. However, if not and it is supported by TensorFlow Lite Micro, then it falls back on the CPU and execute. |