monocular | discovery UI for Helm Chart repositories | Continuous Deployment library
kandi X-RAY | monocular Summary
kandi X-RAY | monocular Summary
Monocular is a web-based application that enables the search and discovery of charts from multiple Helm Chart repositories. It is the codebase that powers the Helm Hub project. Click here to learn more about Helm, Charts and Kubernetes.
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QUESTION
Pytorch documentation provides a concise way to apply MiDaS monocular depth estimation network for depth extraction. But how should I modify their code to extract network representation at some intermediate layer? I know that I could download the model from github and modify forward function to return what I want, but I am interested in the simplest solution, leaving outer code as is.
I'm aware of subclassing the model class and writing my own forward function, like here, but I don't know how to access the class in the code. The model instance is created straight away with midas = torch.hub.load("intel-isl/MiDaS", model_type). Maybe an example of using a forward hook will be easier.
ANSWER
Answered 2021-Jul-15 at 14:52As you said, using a forward hook on a nn.Module is the easiest way to go about it. Consider the documentation: https://pytorch.org/docs/stable/generated/torch.nn.Module.html#torch.nn.Module.register_forward_hook
Basically you just have to define a function that takes three inputs (module, input, output) and then does whatever you want with that data. To find at what Module you want to place that hook you obviously need to be familiar with the structure of the model. You can just print(midas) to get a pretty-printed representation of all the modules available. I just chose some random one, and used the print() function as a hook:
QUESTION
I am trying to compile this version of ORB SLAM2 and after fixing some library import errors, I got this:
...ANSWER
Answered 2021-Apr-22 at 14:53This is an annoying compatibility error. The ORB SLAM you are trying to use only works with Ubuntu 18.04. But, on the ROS ORB SLAM page, they have a new one called orb_slam_ros (click here) that does the same thing.
NOTE: The new one doesn't say that it outputs ROS maps but using Octomap, you can convert a PointCloud to a Map. NOTE: This is tested in Ubuntu 20.04 ROS Noetic. As of now, 20.10 doesn't work.
QUESTION
ANSWER
Answered 2020-Sep-30 at 07:15Strictly speaking, you can't because the ball could be anywhere along the ray to the observer. To some extent you can use the apparent ball diameter to estimate the distance to the observer, but this will be pretty inaccurate. If the ball is measured close to the player, you'd better rely on the player's anatomy.
Another option is to determine the location of the feet of the player, as you known that they rest on the ground plane, and you can use the white lines as a reference. Then you can admit that the ball is at the vertical of a foot.
In any case, you need to be familiar with projective geometry and calibration techniques.
Yet another option is to use a camera that is far away and pointing horizontally (ideally with a telecentric lens, but this is not affordable). In this case, all points of equal height appear approximately on the same horizontal on the image.
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