In the last two decades, computer vision technology has progressed from a mere concept to a breakthrough. Nonetheless, despite advancements, image recognition and object recognition models face significant challenges in everyday life. One of the most significant drawbacks of image recognition and computer vision is the scarcity of datasets. Because there is a data shortage at every end, training image recognition models to produce results with 100 percent accuracy is nearly impossible. Fortunately, OpenAI’s new machine learning model can bridge the technological gap. DALLE 2 can generate visually stunning images from text descriptions. This artificial image creation can provide data to image recognition models based on their requirements.
DALLE 2:
DALLE 2 is the predecessor to DALLE, which can provide images of higher quality and larger size. It is a generative model capable of producing complex images from text descriptions. For instance, if you say ‘a rabbit sitting on the moon with a carrot in hand near an alien,’ it will generate a seamless image based on the text. DALLE 2 can not only create stunning images, but it can also edit them.
Image Recognition Difficulties:
A significant barrier to object and image recognition is a lack of data. In the digital world, datasets can be found everywhere, but here we are, looking for shortcuts to feed the AI model for it to produce good results. However, training an image recognition model is a difficult task. It needs a large amount of data with minor variations, which we may not be able to find easily.
So, what’s the answer?
DALLE 2 is the solution. The OpenAI image generator, with its ability to generate images from text and edit existing ones, can serve as a fill-in tool. This will aid in the generation of more training data while also reducing the need for human labeling.
Despite the significant benefit, users should be wary of false image creations and images that exclude inclusion. This could lead to image detection models producing biased results.
