maskrcnn

Mask R-CNN

input

(from https://github.com/onnx/models/blob/master/vision/object_detection_segmentation/mask-rcnn/dependencies/demo.jpg)

output

usage

Automatically downloads the onnx and prototxt files on the first run. It is necessary to be connected to the Internet while downloading.

For the sample image,

$ python3 maskrcnn.py

If you want to specify the input image, put the image path after the --input option.
You can use --savepath option to change the name of the output file to save.

$ python3 maskrcnn.py --input IMAGE_PATH --savepath SAVE_IMAGE_PATH

By adding the --video option, you can input the video.
If you pass 0 as an argument to VIDEO_PATH, you can use the webcam input instead of the video file.

$ python3 maskrcnn.py --video VIDEO_PATH

Reference

Mask R-CNN : real-time neural network for object instance segmentation

Framework

ONNX Runtime

Model Format

ONNX opset = 10

Netron

• mask_rcnn_R_50_FPN_1x.onnx.prototxt
• mask_rcnn_R_50_FPN_1x.opt.onnx.prototxt