Task:

Load the Lobster dataset from "lobster/data/lobster_301x324x56_uint8.raw", the information about this dataset:
Lobster
Description: CT scan of a lobster contained in a block of resin.
Data Type: uint8
Data Byte Order: little Endian
Data Spacing: 1x1x1.4
Data Extent: 301x324x56
Data loading is very important, make sure you correctly load the dataset according to their features.

Visualize the scanned specimen:
1. Create an isosurface at the specimen boundary, find a proper isovalue to show the whole structure.

2. Use natural colors appropriate for the specimen (red-orange for lobster)

3. Analyze the visualization and answer the following questions:

Q1: Based on the isosurface visualization of the lobster specimen, how many walking legs are visible?
A. 6 walking legs
B. 7 walking legs
C. 8 walking legs
D. 10 walking legs

4. Use a white background. Find an optimal view. Render at 1280x1280. Do not show a color bar or coordinate axes.

5. Set the viewpoint parameters as: [543.52, -957.0, 1007.87] to position; [150.0, 161.5, 38.5] to focal point; [-0.15, 0.62, 0.77] to camera up direction.

6. Save your work:
Save the visualization image as "lobster/results/{agent_mode}/lobster.png".
Save the answers to the analysis questions in plain text as "lobster/results/{agent_mode}/answers.txt".
(Optional, but must save if use paraview) Save the paraview state as "lobster/results/{agent_mode}/lobster.pvsm".
(Optional, but must save if use pvpython script) Save the python script as "lobster/results/{agent_mode}/lobster.py".
(Optional, but must save if use VTK) Save the cxx code script as "lobster/results/{agent_mode}/lobster.cxx"
Do not save any other files, and always save the visualization image and the text file.