Fix: Resolves memory leak caused by using CRAFT detector with detect() or readtext().

[daniellovera]

This fix enables garbage collection to appropriately work when https://github.com/JaidedAI/EasyOCR/blob/c999505ef6b43be1c4ee36aa04ad979175178352/easyocr/detection.py#L24 returns, by deleting the objects we moved to the GPU after we move the forward pass results back on the CPU.

See https://pytorch.org/blog/understanding-gpu-memory-2/#why-doesnt-automatic-garbage-collection-work for more detail.

Running torch.cuda.empty_cache() in test_net() before returning allows nvidia-smi to be accurate.

Interestingly, nvidia-smi showed that GPU memory usage per process was 204MiB upon reader initialization, and then would increase to 234MiB or 288MiB after running easyocr.reader.detect(), but then not increase beyond that point and in some cases reduce back down to 234MiB. I think this has something to do with

One note is that I tested this on a single GPU machine where I changed https://github.com/JaidedAI/EasyOCR/blob/c999505ef6b43be1c4ee36aa04ad979175178352/easyocr/detection.py#L86 to be net = net.to(device), removing DataParallel. There's no reason this shouldn't work on multi-GPU machines, but noting it wasn't tested on one.

I also only tested this on the CRAFT detector, not DBNet.

Relevant package versions easyocr version 1.7.1 torch version 2.2.1+cu121 torchvision 0.17.1+cu121

Hope this helps!