$ ck pull repo:ck-object-detection
$ ck pull repo: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}
Or you can choose from different available version of TensorFlow packages:
$ ck install package --tags=lib,tensorflow
$ ck install ck-tensorflow:package:tensorflowmodel-api
Install one or more object detection model package:
$ ck install package --tags=tensorflowmodel,object-detection
0) tensorflowmodel-object-detection-ssd-resnet50-v1-fpn-sbp-640x640-coco Version 20170714 (09baac5e6f931db2)
1) tensorflowmodel-object-detection-ssd-mobilenet-v1-coco Version 20170714 (385831f88e61be8c)
$ ck install package --tags=dataset,object-detection
NB: If you have previously installed the coco
dataset, you should probably renew them:
$ ck refresh env:{dataset-env-uoa}
where dataset-env-uoa
is one of the env identifiers returned by:
$ ck show env --tags=dataset,coco
$ ck run program:ck-mlperf-tf-object-detection
CK_BATCH_COUNT
The number of batches to be processed.
Default: 1
CK_BATCH_SIZE
The number of images in each batch
Default: 1
CK_ENV_TENSORFLOW_MODEL_FROZEN_GRAPH
The path to the graph to run the inference
Default: set by CK
CK_ENV_TENSORFLOW_MODEL_LABELMAP_FILE
File with the model labelmap file
Default: set by CK
CK_ENV_TENSORFLOW_MODEL_DATASET_TYPE
Type of the dataset (coco,kitti,...) that is used for the inference
Default: set by CK
CK_ENV_IMAGE_WIDTH
and CK_ENV_IMAGE_HEIGHT
The dimensions for the resize of the images, for the preprocessing
Default: set by CK, according to the selected model
CK_ENV_DATASET_IMAGE_DIR
Path to the directory with the images
Default: set by CK
CK_ENV_DATASET_TYPE
Type of dataset used for the program run
Default: set by CK
CK_ENV_DATASET_ANNOTATIONS_PATH
Path to the file with the annotations
Default: set by CK
CK_PROFILE
mlperf profile to select for the run
Default: default_tf_object_det_zoo
CK_SCENARIO
mlperf scenario of the run
Default: Offline
CK_NUM_THREADS
Number of threads used in mlperf
Default: 1
CK_TIME
mlperf parameter time to scan in seconds
Default: 60
CK_QPS
mlperf target qps estimate
Default: 100
CK_ACCURACY
mlperf variable used to enable the accuracy pass
Default: 'YES'
CK_CACHE
mlperf variable used to enable the reuse of preprocessed numpy files. enable ONLY when processing the same model in more than 1 run
Default: 0
CK_QUERIES_SINGLE
CK_QUERIES_MULTI
CK_QUERIES_OFFLINE
mlperf variables with the queries for the different scenarios
Defaults: 1024
24576
24576
CK_MAX_LATENCY
mlperf variable with the max latency in the 99pct tile
Default: 0.1