Google Git
Sign in
opensecura / ml-models-public / 9c58c88cc07da691339a4171fc0cc61048ecf2fe
commit9c58c88cc07da691339a4171fc0cc61048ecf2fe[log] [tgz]
authorLun Dong <lundong@google.com>Sun Aug 06 19:08:59 2023 -0700
committerLun Dong <lundong@google.com>Sun Aug 06 19:08:59 2023 -0700
treef3c059d30ea64e4bb46f2e8cd5587fa2387533dc
parent3df790b5af5ac4592fe22c8c880b548be235c567 [diff]
ml/ml-models-public: do not buid slow targets for kelvin

Do not build VMVX targets for Kelvin as they are very slow.

Change-Id: I150294f71185313f1652f0821602a5cd37cbe290
1 file changed
tree: f3c059d30ea64e4bb46f2e8cd5587fa2387533dc
  1. float_models/
  2. quant_models/
  3. test_data/
  4. CMakeLists.txt
  5. README.md
README.md

Public ML model zoo

This is the model zoo for public models used in Shodan vector core examples.

Model discription

person_detection.tflite

The person presence detection quantized model from https://github.com/tensorflow/tflite-micro/blob/main/tensorflow/lite/micro/models/person_detect.tflite

mobilenet_v1_0.25_224_float.tflite

Mobilenet V1 float-point model from https://tfhub.dev/tensorflow/lite-model/mobilenet_v1_0.25_224/1/default/1?lite-format=tflite

mobilenet_v1_0.25_224_quant.tflite

Mobilenet V1 quantized model from https://tfhub.dev/tensorflow/lite-model/mobilenet_v1_0.25_224_quantized/1/default/1?lite-format=tflite

mobilenet_v2_1.0_224_quant.tflite

Mobilenet V2 quantized model from https://tfhub.dev/tensorflow/lite-model/mobilenet_v2_1.0_224_quantized/1/default/1?lite-format=tflite

hps_quant.tflite

HPS (Human Presence Sensor) non-tiled quantized model from https://chromium.googlesource.com/chromiumos/platform/hps-firmware/+/6cdea6d1158a8cd3238b8ae4f744fdb494779c80/models/shared.tflite

Visualize the model

For tflite models, use the web-based visualization tool to inspect the file. The tool supports drag and drop or file GUI.

Test data

Test data for sample model inputs are in the “test_data” directory. Currently, only test data for the Human Presence Sensor model are included.

hps_0-6.jpg

Test image files for Human Presence Sensor model, from ChromeOS codebase.

Model executables

For each model, the corresponding model executable under iree_exec can be built with the .c/.h files using sw/vec_iree project as library. They can be run as unit tests via lit framework using Renode or QEMU.