Open arminak6 opened 2 months ago
Hi, congrats on the fantastic work! These results are amazing. To address the issue of RAM usage with large datasets, is there a technique available to concatenate two outputs in case of overlap? something like this:
` output1 = inference(pairs1, model, device, batch_size=batch_size) scene1 = global_aligner(output1, device=device, mode=GlobalAlignerMode.PointCloudOptimizer)
output2 = inference(pairs2, model, device, batch_size=batch_size) scene2 = global_aligner(output2, device=device, mode=GlobalAlignerMode.PointCloudOptimizer) `
Then concatenate scene1 and scene2 together?
Thanks again for the wonderful work!
Hi, congrats on the fantastic work! These results are amazing. To address the issue of RAM usage with large datasets, is there a technique available to concatenate two outputs in case of overlap? something like this:
` output1 = inference(pairs1, model, device, batch_size=batch_size) scene1 = global_aligner(output1, device=device, mode=GlobalAlignerMode.PointCloudOptimizer)
output2 = inference(pairs2, model, device, batch_size=batch_size) scene2 = global_aligner(output2, device=device, mode=GlobalAlignerMode.PointCloudOptimizer) `
Then concatenate scene1 and scene2 together?
Thanks again for the wonderful work!