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authorÉanna Ó Catháin <eanna.ocathain@arm.com>2021-09-15 09:32:30 +0100
committerKshitij Sisodia <kshitij.sisodia@arm.com>2021-09-16 16:01:23 +0100
commit8f9588721cbb7356b03a714c97d6b3a9a6e89438 (patch)
tree1ca19d31958081c09f360d91e15fefb6e38b3992 /docs/documentation.md
parente6588f620c648dd0492f6133152855d77c672568 (diff)
downloadml-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>
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@@ -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.