diff --git a/CHANGELOG.md b/CHANGELOG.md index 27d2e821e64..4a65a4b626a 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -27,6 +27,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 - React & Redux & Antd based dashboard - Yolov3 interpretation script fix and changes to mapping.json - YOLO format support ([#1151](https://github.com/opencv/cvat/pull/1151)) +- Added support for OpenVINO 2020 ### Deprecated - diff --git a/cvat/apps/auto_annotation/inference_engine.py b/cvat/apps/auto_annotation/inference_engine.py index 310e78c45be..fb6b543d34e 100644 --- a/cvat/apps/auto_annotation/inference_engine.py +++ b/cvat/apps/auto_annotation/inference_engine.py @@ -2,7 +2,7 @@ # # SPDX-License-Identifier: MIT -from openvino.inference_engine import IENetwork, IEPlugin +from openvino.inference_engine import IENetwork, IEPlugin, IECore, get_version import subprocess import os @@ -19,7 +19,20 @@ def _check_instruction(instruction): ) -def make_plugin(): +def make_plugin_or_core(): + version = get_version() + use_core_openvino = False + try: + major, minor, reference = [int(x) for x in version.split('.')] + if major >= 2 and minor >= 1 and reference >= 37988: + use_core_openvino = True + except Exception: + pass + + if use_core_openvino: + ie = IECore() + return ie + if _IE_PLUGINS_PATH is None: raise OSError('Inference engine plugin path env not found in the system.') diff --git a/cvat/apps/auto_annotation/model_loader.py b/cvat/apps/auto_annotation/model_loader.py index cb923a9cada..e48d5c8e4d1 100644 --- a/cvat/apps/auto_annotation/model_loader.py +++ b/cvat/apps/auto_annotation/model_loader.py @@ -8,25 +8,22 @@ import os import numpy as np -from cvat.apps.auto_annotation.inference_engine import make_plugin, make_network +from cvat.apps.auto_annotation.inference_engine import make_plugin_or_core, make_network class ModelLoader(): def __init__(self, model, weights): self._model = model self._weights = weights - IE_PLUGINS_PATH = os.getenv("IE_PLUGINS_PATH") - if not IE_PLUGINS_PATH: - raise OSError("Inference engine plugin path env not found in the system.") - - plugin = make_plugin() + core_or_plugin = make_plugin_or_core() network = make_network(self._model, self._weights) - supported_layers = plugin.get_supported_layers(network) - not_supported_layers = [l for l in network.layers.keys() if l not in supported_layers] - if len(not_supported_layers) != 0: - raise Exception("Following layers are not supported by the plugin for specified device {}:\n {}". - format(plugin.device, ", ".join(not_supported_layers))) + if getattr(core_or_plugin, 'get_supported_layers', False): + supported_layers = core_or_plugin.get_supported_layers(network) + not_supported_layers = [l for l in network.layers.keys() if l not in supported_layers] + if len(not_supported_layers) != 0: + raise Exception("Following layers are not supported by the plugin for specified device {}:\n {}". + format(core_or_plugin.device, ", ".join(not_supported_layers))) iter_inputs = iter(network.inputs) self._input_blob_name = next(iter_inputs) @@ -45,7 +42,12 @@ def __init__(self, model, weights): if self._input_blob_name in info_names: self._input_blob_name = next(iter_inputs) - self._net = plugin.load(network=network, num_requests=2) + if getattr(core_or_plugin, 'load_network', False): + self._net = core_or_plugin.load_network(network, + "CPU", + num_requests=2) + else: + self._net = core_or_plugin.load(network=network, num_requests=2) input_type = network.inputs[self._input_blob_name] self._input_layout = input_type if isinstance(input_type, list) else input_type.shape diff --git a/cvat/apps/dextr_segmentation/dextr.py b/cvat/apps/dextr_segmentation/dextr.py index 703c6d08398..628961ff576 100644 --- a/cvat/apps/dextr_segmentation/dextr.py +++ b/cvat/apps/dextr_segmentation/dextr.py @@ -3,7 +3,7 @@ # # SPDX-License-Identifier: MIT -from cvat.apps.auto_annotation.inference_engine import make_plugin, make_network +from cvat.apps.auto_annotation.inference_engine import make_plugin_or_core, make_network import os import cv2 @@ -32,12 +32,15 @@ def __init__(self): def handle(self, im_path, points): # Lazy initialization if not self._plugin: - self._plugin = make_plugin() + self._plugin = make_plugin_or_core() self._network = make_network(os.path.join(_DEXTR_MODEL_DIR, 'dextr.xml'), os.path.join(_DEXTR_MODEL_DIR, 'dextr.bin')) self._input_blob = next(iter(self._network.inputs)) self._output_blob = next(iter(self._network.outputs)) - self._exec_network = self._plugin.load(network=self._network) + if getattr(self._plugin, 'load_network', False): + self._exec_network = self._plugin.load_network(self._network, 'CPU') + else: + self._exec_network = self._plugin.load(network=self._network) image = PIL.Image.open(im_path) numpy_image = np.array(image) diff --git a/cvat/apps/tf_annotation/views.py b/cvat/apps/tf_annotation/views.py index 2a70c9db323..4aa0589cae6 100644 --- a/cvat/apps/tf_annotation/views.py +++ b/cvat/apps/tf_annotation/views.py @@ -30,7 +30,7 @@ def load_image_into_numpy(image): def run_inference_engine_annotation(image_list, labels_mapping, treshold): - from cvat.apps.auto_annotation.inference_engine import make_plugin, make_network + from cvat.apps.auto_annotation.inference_engine import make_plugin_or_core, make_network def _normalize_box(box, w, h, dw, dh): xmin = min(int(box[0] * dw * w), w) @@ -44,11 +44,14 @@ def _normalize_box(box, w, h, dw, dh): if MODEL_PATH is None: raise OSError('Model path env not found in the system.') - plugin = make_plugin() + core_or_plugin = make_plugin_or_core() network = make_network('{}.xml'.format(MODEL_PATH), '{}.bin'.format(MODEL_PATH)) input_blob_name = next(iter(network.inputs)) output_blob_name = next(iter(network.outputs)) - executable_network = plugin.load(network=network) + if getattr(core_or_plugin, 'load_network', False): + executable_network = core_or_plugin.load_network(network, 'CPU') + else: + executable_network = core_or_plugin.load(network=network) job = rq.get_current_job() del network