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https://github.com/graphdeco-inria/gaussian-splatting
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fixed tensorboard update images by adding batch dimension (#9)
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4
train.py
4
train.py
@ -162,9 +162,9 @@ def training_report(tb_writer, iteration, Ll1, loss, l1_loss, elapsed, testing_i
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images = torch.cat((images, image.unsqueeze(0)), dim=0)
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images = torch.cat((images, image.unsqueeze(0)), dim=0)
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gts = torch.cat((gts, gt_image.unsqueeze(0)), dim=0)
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gts = torch.cat((gts, gt_image.unsqueeze(0)), dim=0)
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if tb_writer and (idx < 5):
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if tb_writer and (idx < 5):
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tb_writer.add_images(config['name'] + "_view_{}/render".format(viewpoint.image_name), image, global_step=iteration)
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tb_writer.add_images(config['name'] + "_view_{}/render".format(viewpoint.image_name), image[None], global_step=iteration)
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if iteration == testing_iterations[0]:
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if iteration == testing_iterations[0]:
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tb_writer.add_images(config['name'] + "_view_{}/ground_truth".format(viewpoint.image_name), gt_image, global_step=iteration)
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tb_writer.add_images(config['name'] + "_view_{}/ground_truth".format(viewpoint.image_name), gt_image[None], global_step=iteration)
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l1_test = l1_loss(images, gts)
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l1_test = l1_loss(images, gts)
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psnr_test = psnr(images, gts).mean()
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psnr_test = psnr(images, gts).mean()
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