This custom node analyses the response of models from OpenVINO Model Zoo. Based on the inference results and the original image, it generates a list of detected boxes for following object recognition models. Each image in the output will be resized to the predefined target size to fit the input of the next model in the DAG pipeline. Additionally to the detected text boxes, two additional outputs are returned - information about coordinates and confidence levels of each box detection.
All OpenVINO Model Zoo object detection models with specific output tensor detection with shape: [1, 1, 200, 7]:
- face-detection
- face-detection-adas
- face-detection-retail
- person-detection
- person-detection-adas
- person-detection-retail
- vehicle-detection
- vehicle-detection-adas
- product-detection
- person-vehicle-bike-detection
- vehicle-license-plate-detection
- pedestrian-and-vehicle-detector
You can build the shared library of the custom node simply by running command in this custom node folder context:
make
It will compile the library inside a docker container and save the results in lib folder.
| Input name | Description | Shape | Precision |
|---|---|---|---|
| image | Input image in an array format. Only batch size 1 is supported and images must have 3 channels. Resolution is configurable via parameters original_image_width and original_image_height. Color data required only in BGR format. |
1,3,H,W |
FP32 |
| detection | object detection model output | 1,1,200,7 |
FP32 |
| Output name | Description | Shape | Precision |
|---|---|---|---|
| images | Returns images representing detected text boxes. Boxes are filtered based on confidence_threshold param. Resolution is defined by the node parameters. All images are in a single batch. Batch size depend on the number of detected objects. | N,1,C,H,W |
FP32 |
| coordinates | For every detected box N the following info is added: x coordinate for the box center, y coordinate for the box center, box original width, box original height |
N,1,4 |
I32 |
| confidences | For every detected box N information about confidence level (N - number of detected boxes; more about demultiplexing here) |
N,1,1 |
FP32 |
Parameters can be defined in pipeline definition in OVMS configuration file. Read more about node parameters.
| Parameter | Description | Default | Required |
|---|---|---|---|
| original_image_width | Required input image width | ✓ | |
| original_image_height | Required input image height | ✓ | |
| target_image_width | Target width of the boxes in output. Boxes in the original image will be resized to that value. | ✓ | |
| target_image_height | Target width of the boxes in output. Boxes in the original image will be resized to that value. | ✓ | |
| original_image_layout | Defines input image layout | NCHW | |
| target_image_layout | Defines the data layout of detected object images in the node output | NCHW | |
| convert_to_gray_scale | Defines if output images should be in grayscale or in color | false | |
| confidence_threshold | Number in a range of 0-1 | ✓ | |
| debug | Defines if debug messages should be displayed | false | |
| max_output_batch | Prevents too big batches with incorrect confidence level. It can avoid exceeding RAM resources | 100 | |
| filter_label_id | For object detection models with multiple label IDs results, use this parameter to filter the ones with desired ID |