Method of and system for generating training images for instance segmentation machine learning algorithm

A method for training an instance segmentation machine learning algorithm (MLA), the method being executed by a processor, the processor having access to:

• a classification MLA having been trained to detect objects in an image and generate a class activation map (CAM) indicative of discriminative regions used for detecting the objects,
• a region proposal MLA having been trained to generate region proposals from an image, and
• the instance segmentation MLA,
• the method comprising:
• receiving a set of image-level labelled images, each image-level labelled image comprising a respective object class label indicative of a presence of a respective object having a respective object class in the image;
• detecting, using the classification MLA, in each image-level labelled image, the respective object having the respective object class, the detecting comprising generating a respective CAM indicative of discriminative regions used by the classification MLA to detect the respective object class;
• generating, using the region proposal MLA, for each image-level labelled image of the set of image-level labelled images, a respective set of region proposals, each region proposal comprising a respective potential object;
• generating, for each image-level labelled image of the set of image-level labelled images, based on the respective CAM and the respective set of region proposals, a respective pseudo mask of the respective object indicative of pixels in the image-level labelled image corresponding to the respective object class;
• and
• training an instance segmentation MLA on the set of image-level labelled images and the respective pseudo masks by using the respective pseudo mask having the respective object class label as a target.

A system for generating a set of training images for training an instance segmentation machine learning algorithm (MLA), the system comprising a processor, the processor having access to:

• a classification MLA having been trained to detect objects in an image and generate a class activation map (CAM) indicative of discriminative regions used for detecting the objects,
• a region proposal MLA having been trained to generate region proposals from an image,
• the processor being operatively connected to a non-transitory storage medium comprising instructions;
• the processor, upon executing the instructions, being configured for:
• receiving a set of image-level labelled images, each image-level labelled image comprising an object class label indicative of a presence of a respective object having a respective object class in the image;
• detecting, using the classification MLA, in each image-level labelled image, the respective object having the respective object class;
• determining, using the classification MLA, for each image-level labelled image of the set of image-level labelled images, a respective CAM indicative of discriminative regions used by the classification MLA to detect the respective object class;
• generating, using the region proposal MLA, for each image-level labelled image of the set of image-level labelled images, a respective set of region proposals, each region proposal comprising a respective potential object;
• generating, for each image-level labelled image of the set of image-level labelled images, based on the respective CAM and the respective set of region proposals, a respective pseudo mask of the respective object indicative of pixels in the image-level labelled image corresponding to the respective object class;
• and
• generating a set of training images to be provided for training an instance segmentation MLA, each training image comprising:
• a respective object class of the respective object, and
• the respective pseudo mask of the respective object having the respective object class.