Open booker-max opened 1 year ago
Hi, thanks for looking at the code.
Right out of the dataloader, the shape of data['R'] is (1, B, 3, 3) since we load one scene per iteration.
Render batch size is the batch size for target_pose and target_image. The forward for relative_cam takes in all cameras and pose from dataloader, and based on batch_idx == query_idx, it picks of the target_image and target_pose. It also randomly selects the context_image and context_pose.
In the output of the last line in your code box can be interpreted as this:
**What a great job this is!
I have some problems, mainly inside EFT
target_cameras = PerspectiveCameras(R=data['R'][0],T=data['T'][0],focal_length=data['f'][0],principal_point=data['c'][0],image_size=data['image_size'][0]).cuda(gpu) target_rgb = data['images'][0].cuda(gpu)
2. I don't really understand what sample batch cameras do, what does the code mean by setting render_batch_size=1 and query_idx? I'm not sure I understand. Don't you just need to input context_size, a reference pose and reference_image, and a target_pose to output a target_image?