Machine vision systems and methods for automatically generating one or more machine vision jobs based on region of interests (ROIs) of digital images

A machine vision system configured to automatically generate one or more machine vision jobs based on region of interests (ROIs) of digital images, the machine vision system comprising:

• an imaging device configured to implement one or more machine vision jobs;
• one or more processors;
• and
• a memory communicatively coupled to the one or more processors and storing computing instructions that when executed by the one or more processors, cause the one or more processors to:
• configure a machine vision tool for capturing an image identifier (ID),
• load a plurality of training images, each training image depicting the image ID,
• label each of the plurality of training images to indicate a success status or a failure status of an object depicted within each training image,
• extract one or more candidate image features from the plurality of training images,
• generate one or more candidate ROIs based on the candidate image features,
• select a training set of ROIs from the one or more candidate ROIs, wherein each ROI of the training set of ROIs is designated as an included ROI or an excluded ROI, and
• train, with the training set of ROIs and the plurality of training images, a vision learning model,
• wherein the vision learning model is configured to output a machine vision job,
• wherein the machine vision job is configured for electronic deployment to the imaging device, and
• wherein the imaging device, implementing the machine vision job, is configured to detect the success status or the failure status of additional images depicting the object.

A tangible, non-transitory computer-readable medium storing computing instructions for automatically generating one or more machine vision jobs based on region of interests (ROIs) of digital images, that when executed by one or more processors cause the one or more processors to:

• configure a machine vision tool for capturing an image ID;
• load a plurality of training images, each training image depicting the image identifier (ID);
• label each of the plurality of training images to indicate a success status or a failure status of an object depicted within each training image;
• extract one or more candidate image features from the plurality of training images;
• generate one or more candidate ROIs based on the candidate image features;
• select a training set of ROIs from the one or more candidate ROIs, wherein each ROI of the training set of ROIs is designated as an included ROI or an excluded ROI;
• and
• train, with the training set of ROIs and the plurality of training images, a vision learning model,
• wherein the vision learning model is configured to output a machine vision job,
• wherein the machine vision job is configured for electronic deployment to an imaging device, and
• wherein the imaging device, implementing the machine vision job, is configured to detect the success status or the failure status of additional images depicting the object.