2bf8d910f6
* [Docs][PyOV] update python snippets * first snippet * Fix samples debug * Fix linter * part1 * Fix speech sample * update model state snippet * add serialize * add temp dir * CPU snippets update (#134) * snippets CPU 1/6 * snippets CPU 2/6 * snippets CPU 3/6 * snippets CPU 4/6 * snippets CPU 5/6 * snippets CPU 6/6 * make module TODO: REMEMBER ABOUT EXPORTING PYTONPATH ON CIs ETC * Add static model creation in snippets for CPU * export_comp_model done * leftovers * apply comments * apply comments -- properties * small fixes * rempve debug info * return IENetwork instead of Function * apply comments * revert precision change in common snippets * update opset * [PyOV] Edit docs for the rest of plugins (#136) * modify main.py * GNA snippets * GPU snippets * AUTO snippets * MULTI snippets * HETERO snippets * Added properties * update gna * more samples * Update docs/OV_Runtime_UG/model_state_intro.md * Update docs/OV_Runtime_UG/model_state_intro.md * attempt1 fix ci * new approach to test * temporary remove some files from run * revert cmake changes * fix ci * fix snippet * fix py_exclusive snippet * fix preprocessing snippet * clean-up main * remove numpy installation in gha * check for GPU * add logger * iexclude main * main update * temp * Temp2 * Temp2 * temp * Revert temp * add property execution devices * hide output from samples --------- Co-authored-by: p-wysocki <przemyslaw.wysocki@intel.com> Co-authored-by: Jan Iwaszkiewicz <jan.iwaszkiewicz@intel.com> Co-authored-by: Karol Blaszczak <karol.blaszczak@intel.com>
103 lines
3.0 KiB
Python
103 lines
3.0 KiB
Python
# Copyright (C) 2018-2023 Intel Corporation
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
|
|
from utils import get_model, get_ngraph_model
|
|
|
|
#! [ov_imports]
|
|
from openvino import Core, Layout, Type
|
|
from openvino.preprocess import ColorFormat, PrePostProcessor, ResizeAlgorithm
|
|
#! [ov_imports]
|
|
|
|
#! [imports]
|
|
import openvino.inference_engine as ie
|
|
#! [imports]
|
|
|
|
#include "inference_engine.hpp"
|
|
|
|
tensor_name="input"
|
|
core = Core()
|
|
model = get_model([1,32,32,3])
|
|
|
|
#! [ov_mean_scale]
|
|
ppp = PrePostProcessor(model)
|
|
input = ppp.input(tensor_name)
|
|
# we only need to know where is C dimension
|
|
input.model().set_layout(Layout('...C'))
|
|
# specify scale and mean values, order of operations is important
|
|
input.preprocess().mean([116.78]).scale([57.21, 57.45, 57.73])
|
|
# insert preprocessing operations to the 'model'
|
|
model = ppp.build()
|
|
#! [ov_mean_scale]
|
|
|
|
model = get_model()
|
|
|
|
#! [ov_conversions]
|
|
ppp = PrePostProcessor(model)
|
|
input = ppp.input(tensor_name)
|
|
input.tensor().set_layout(Layout('NCHW')).set_element_type(Type.u8)
|
|
input.model().set_layout(Layout('NCHW'))
|
|
# layout and precision conversion is inserted automatically,
|
|
# because tensor format != model input format
|
|
model = ppp.build()
|
|
#! [ov_conversions]
|
|
|
|
#! [ov_color_space]
|
|
ppp = PrePostProcessor(model)
|
|
input = ppp.input(tensor_name)
|
|
input.tensor().set_color_format(ColorFormat.NV12_TWO_PLANES)
|
|
# add NV12 to BGR conversion
|
|
input.preprocess().convert_color(ColorFormat.BGR)
|
|
# and insert operations to the model
|
|
model = ppp.build()
|
|
#! [ov_color_space]
|
|
|
|
model = get_model([1, 3, 448, 448])
|
|
|
|
#! [ov_image_scale]
|
|
ppp = PrePostProcessor(model)
|
|
input = ppp.input("input")
|
|
# need to specify H and W dimensions in model, others are not important
|
|
input.model().set_layout(Layout('??HW'))
|
|
# scale to model shape
|
|
input.preprocess().resize(ResizeAlgorithm.RESIZE_LINEAR, 448, 448)
|
|
# and insert operations to the model
|
|
model = ppp.build()
|
|
#! [ov_image_scale]
|
|
|
|
import openvino.inference_engine as ie
|
|
import ngraph as ng
|
|
|
|
operation_name = "data"
|
|
|
|
core = ie.IECore()
|
|
network = get_ngraph_model()
|
|
|
|
|
|
#! [mean_scale]
|
|
preprocess_info = network.input_info[operation_name].preprocess_info
|
|
preprocess_info.init(3)
|
|
preprocess_info[0].mean_value = 116.78
|
|
preprocess_info[1].mean_value = 116.78
|
|
preprocess_info[2].mean_value = 116.78
|
|
preprocess_info[0].std_scale = 57.21
|
|
preprocess_info[1].std_scale = 57.45
|
|
preprocess_info[2].std_scale = 57.73
|
|
preprocess_info.mean_variant = ie.MeanVariant.MEAN_VALUE
|
|
#! [mean_scale]
|
|
|
|
#! [conversions]
|
|
input_info = network.input_info[operation_name]
|
|
input_info.precision = "U8"
|
|
input_info.layout = "NHWC"
|
|
# model input layout is always NCHW in Inference Engine
|
|
# for shapes with 4 dimensions
|
|
#! [conversions]
|
|
|
|
#! [image_scale]
|
|
preprocess_info = network.input_info[operation_name].preprocess_info
|
|
# Inference Engine supposes input for resize is always in NCHW layout
|
|
# while for OpenVINO Runtime API 2.0 `H` and `W` dimensions must be specified
|
|
# Also, current code snippet supposed resize from dynamic shapes
|
|
preprocess_info.resize_algorithm = ie.ResizeAlgorithm.RESIZE_BILINEAR
|