To make this process easier, there are a lot of programs exist to visually annotate images for machine learning. You can ask a search engine something like "software to annotate images for machine learning" to get a list of them. There are also many online tools that can do all this work. One of the great online tools for this is the Roboflow Annotate. Using this service, you just need to upload your images, draw... - Source: dev.to / 12 months ago

I haven't used their product but looking at their website it looks like they are focused on dataset management and the pipeline around that part of the process (uploading data, understanding the data, labeling data, data curation, model assisted labeling) which is what Roboflow does with https://roboflow.com/annotate. Source: over 1 year ago

We’re happy to sponsor personal and academic projects at Roboflow. Just reach out and we’ll hook you up: https://roboflow.com/annotate. Source: almost 3 years ago

At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago

To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago