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README.md
benchmark.nvidia-gtx1080.py
benchmark.nvidia-tx1.py
classify.py

README.md

Pre-requisites

Python 2

Misc

# python -m pip install enum34 mock pillow
# python -m pip install wheel absl-py

SciPy

# apt install liblapack-dev libatlas-dev
# python -m pip install scipy

Install via CK

TensorFlow

Install from source:

$ ck install package:lib-tensorflow-1.10.1-src-{cpu,cuda}

or from a binary x86_64 package:

$ ck install package:lib-tensorflow-1.10.1-{cpu,cuda}

TensorFlow models

$ ck install package:tensorflowmodel-alexnet-py
$ ck install package:tensorflowmodel-squeezenet-py
$ ck install package:tensorflowmodel-googlenet-py
$ ck install package:tensorflowmodel-mobilenet-v1-1.0-224-py
$ ck show env --tags=tensorflowmodel
Env UID:         Target OS: Bits: Name:                                                   Version: Tags:

ef7343498dbec627   linux-64    64 TensorFlow python model and weights (squeezenet)        ImageNet 64bits,host-os-linux-64,python,squeezenet,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
dede2b537d476299   linux-64    64 TensorFlow python model and weights (mobilenet-1.0-224) ImageNet 64bits,host-os-linux-64,mobilenet,mobilenet-v1,mobilenet-v1-1.0-224,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
73619b7df1e2488e   linux-64    64 TensorFlow python model and weights (googlenet)         ImageNet 64bits,googlenet,host-os-linux-64,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights
4dd098ad717db21d   linux-64    64 TensorFlow python model and weights (alexnet)           ImageNet 64bits,alexnet,host-os-linux-64,python,target-os-linux-64,tensorflow-model,tensorflowmodel,v0,weights

ImageNet dataset

$ ck install package:imagenet-2012-val-min
$ ck install package:imagenet-2012-aux

Benchmark

$ ck list local:experiment:*
$ cd `ck find program:image-classification-tf-py`
$ python benchmark.nvidia-gtx1080.py

Program parameters

CK_TMP_IMAGE_SIZE

Preprocessing parameter, size of intermediate image. If this parameter is set to a value greater than targer image size defined by a model, loaded images will be scaled to this size and then cropped to target size.

For example, when running against MobileNet you may specify --env.CK_TMP_IMAGE_SIZE=256, then images will be resized to 256x256 the cropped to 224x244 as required to MobileNet.

Default: 0

CK_CROP_PERCENT

Preprocessing parameter, percentage of central image region for cropping. If this parameter is set to a value between 0 and 100, loaded images will be cropped to this percent and then scaled to targer image size defined by a model.

Not used if CK_TMP_IMAGE_SIZE is set and valid.

Default: 87.5

CK_SUBTRACT_MEAN

Preprocessing parameter, defines whether program should subtract mean value from loaded image. If CK_USE_MODEL_MEAN is not set then mean value is calculated over all images' pixels.

Default: YES

CK_USE_MODEL_MEAN

Preprocessing parameter, defines whether program should ask a model for mean value that will be subtracted. Model should provide get_mean_value method for this.

Used when CK_SUBTRACT_MEAN is set.

Default: YES

CK_CACHE_IMAGES

Do caching of preprocessed images. Images are cached into a directory whose name contained of preprocessing parameters. Next time when program runs with the same preprocessing parameters, preprocessed images will be loaded from cache. This significantly speeds up images loading process.

Default: YES

CK_RECREATE_CACHE

Is set to YES then existed cached images will be erased.

Default: NO

CK_CACHE_DIR

Root director for storing cached images. This directory will include additional subdirectories for images preprocessed with different preprocessing parameters CK_TMP_IMAGE_SIZE and CK_CROP_PERCENT.

Default: ../preprocessed