The example uses ssd_mobilenet_v1_coco, a multi-object detection model trained on the COCO dataset.
Refer to Tensorflow detection model zoo for more details.
| Node Name | Input/Output | Shape | Data Description |
|---|---|---|---|
| image_tensor | Input | [batch, height, width, 3] | RGB pixel values as uint8 in a square format (Width, Height). The first column represent the batch size. |
| detection_boxes | Output | [batch, num_detections, 4] | Array of boxes for each detected object in the format [yMin, xMin, yMax, xMax] |
| detection_scores | Output | [batch, num_detections] | Array of probability scores for each detected object between 0 and 1 |
| detection_classes | Output | [batch, num_detections] | Array of object class indices for each object detected based on COCO objects |
| num_detections | Output | [batch] | Number of detections |
go run main.go -dir=<model folder> -jpg=<input.jpg> [-out=<output.jpg>] [-labels=<labels.txt>]