Is possible, but if you have the data to generate those images, will be easier to treat the data not as an image (chart)

Hundreds of firms have already tried this years ago- there is no alpha left in this type of information. Source: work at a hedge fund and have friends at two sigma, citadel, and D. E. Shaw. If you want to do it as an academic exercise go ahead, but this is not how you make money.

The approach you are describing isn’t the best.

1. There is no sense in rendering these images as OHLCV data is timeseries, not 2D images. Most of the data would just be white pixels. Which is not really wrong but is greatly inefficient. Instead of using 2D convolutions 1D convolutions can be used on the timeseries directly (which is called a Wavenet) which would remove rendering from your pipeline and greatly speedup training and inference.

2. OHLCV data won’t give you enough information to neither predict the future or backtest your trading algorithm accurately due to loss of data after aggregations.

Agreed, financial markets have built-in protections against this kind of analysis. If it works, everyone else would do it, and the more people do it the less any of them benefit from it.

The only way to beat the market consistently is to have a source of information nobody else has access to, or at least hasn't discovered yet.

This has been done using Gramian Angular Field as images. See here - https://ieeexplore.ieee.org/document/9080613

This is exactly what I would tell others if this worked.

this is great. thanks