## OpenVINO Support

This tutorial is based on Linux systems like Ubuntu-18.04.
### Installation
It is recommended to create a virtual environment for the project.
1. Install [OpenVINO](https://docs.openvino.ai/2021.4/get_started.html). It is recommended to use the installer or install using pip.
Installation example using [pip](https://pypi.org/project/openvino-dev/):
```bash
pip install openvino-dev
```
2. *`Optional` If you want to use OpenVINO in SDK, you need install OpenVINO with [install_guides](https://docs.openvino.ai/2021.4/openvino_docs_install_guides_installing_openvino_linux.html#install-openvino).

3. Install MMDeploy following the [instructions](../build.md).

To work with models from [MMDetection](https://github.com/open-mmlab/mmdetection/blob/master/docs/get_started.md), you may need to install it additionally.

### Troubleshooting

#### ImportError: libpython3.7m.so.1.0: cannot open shared object file: No such file or directory
To resolve missing external dependency on Ubuntu*, execute the following command:
```bash
sudo apt-get install libpython3.7
```

### Usage

Example:
```bash
python tools/deploy.py \
    configs/mmdet/detection/detection_openvino_static-300x300.py \
    /mmdetection_dir/mmdetection/configs/ssd/ssd300_coco.py \
    /tmp/snapshots/ssd300_coco_20210803_015428-d231a06e.pth \
    tests/data/tiger.jpeg \
    --work-dir ../deploy_result \
    --device cpu \
    --log-level INFO
```

### List of supported models exportable to OpenVINO from MMDetection

The table below lists the models that are guaranteed to be exportable to OpenVINO from MMDetection.
|     Model name     |                                  Config                                   | Dynamic Shape |
| :----------------: | :-----------------------------------------------------------------------: | :-----------: |
|        ATSS        |                  `configs/atss/atss_r50_fpn_1x_coco.py`                   |       Y       |
| Cascade Mask R-CNN |        `configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.py`        |       Y       |
|   Cascade R-CNN    |          `configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py`           |       Y       |
|    Faster R-CNN    |           `configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.py`            |       Y       |
|        FCOS        | `configs/fcos/fcos_x101_64x4d_fpn_gn-head_mstrain_640-800_4x2_2x_coco.py` |       Y       |
|      FoveaBox      |             `configs/foveabox/fovea_r50_fpn_4x4_1x_coco.py `              |       Y       |
|        FSAF        |                  `configs/fsaf/fsaf_r50_fpn_1x_coco.py`                   |       Y       |
|     Mask R-CNN     |             `configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.py`              |       Y       |
|     RetinaNet      |             `configs/retinanet/retinanet_r50_fpn_1x_coco.py`              |       Y       |
|        SSD         |                       `configs/ssd/ssd300_coco.py`                        |       Y       |
|       YOLOv3       |            `configs/yolo/yolov3_d53_mstrain-608_273e_coco.py`             |       Y       |
|       YOLOX        |                `configs/yolox/yolox_tiny_8x8_300e_coco.py`                |       Y       |
| Faster R-CNN + DCN |         `configs/dcn/faster_rcnn_r50_fpn_dconv_c3-c5_1x_coco.py`          |       Y       |
|       VFNet        |                 `configs/vfnet/vfnet_r50_fpn_1x_coco.py`                  |       Y       |

Notes:

- Custom operations from OpenVINO use the domain `org.openvinotoolkit`.
- For faster work in OpenVINO in the Faster-RCNN, Mask-RCNN, Cascade-RCNN, Cascade-Mask-RCNN models
the RoiAlign operation is replaced with the [ExperimentalDetectronROIFeatureExtractor](https://docs.openvinotoolkit.org/latest/openvino_docs_ops_detection_ExperimentalDetectronROIFeatureExtractor_6.html) operation in the ONNX graph.
- Models "VFNet" and "Faster R-CNN + DCN" use the custom "DeformableConv2D" operation.

### FAQs

- None