Tutorial: Instantiating a CSM Camera Model from Image¶
Lessons learned in this tutorial: * How to generate Image Support Data (ISD) for an image * instantiate a CSM camera model * Perform a simple ground to image call
1. Prerequisites, Install Knoten¶
The knoten installation may take a little longer than usual due to the many dependencies (including ALE) involved.
2. Generate an ISD from a Cube¶
We will use MRO data located in the data/image_to_ground folder containing a cube and necessary kernels for ISD (Image Support Data) generation.
Note: If your cube already has attached spice data, do you not have to specify kernels in the props param and can pass in an empty dict {} instead.
import ale
import json
import knoten
import os
# Set local data directory and paths
data_dir = '../data/image_to_ground'
cube_file = os.path.join(data_dir, 'B10_013341_1010_XN_79S172W.cub')
isd_file = os.path.join(data_dir, 'isd_file.json')
# Set local kernel paths
props = {
'kernels': [
os.path.join(data_dir, 'B10_013341_1010_XN_79S172W_0.bsp'),
os.path.join(data_dir, 'B10_013341_1010_XN_79S172W_1.bsp'),
os.path.join(data_dir, 'mro_ctx_v11.ti'),
os.path.join(data_dir, 'mro_sc_psp_090526_090601_0_sliced_-74000.bc'),
os.path.join(data_dir, 'mro_sc_psp_090526_090601_1_sliced_-74000.bc'),
os.path.join(data_dir, 'mro_sclkscet_00082_65536.tsc'),
os.path.join(data_dir, 'mro_v16.tf'),
os.path.join(data_dir, 'naif0012.tls'),
os.path.join(data_dir, 'pck00008.tpc')
]
}
# Generate the ISD string from the cube's label
isd_str = ale.loads(
label=cube_file,
formatter="ale",
props=props,
indent=2,
verbose=False,
only_isis_spice=False,
only_naif_spice=False
)
# Write the ISD string to file 'isd_file.json'
with open(isd_file, "w") as file:
file.write(isd_str)
3. Create a Community Sensor Model¶
We will use Knoten's implementation of CSM as the library supports line scanner types of sensor models in the usgscsm library.
4. Convert image coordinates into ground coordinates¶
# Create an image coordinate at line = 206 and sample = 206
image_coord = knoten.csmapi.ImageCoord(206, 206)
# Convert the image coordinates to ground coordinates with desired precision of 0.0
ground_coord = sensor_model.imageToGround(image_coord, 0.0)
# Output the ground coordinates
ground_coord.x, ground_coord.y, ground_coord.z