jaseg/infiray_irg_py
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Correct radiometric kelvin offset for P200

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The P200 uses 273.2K instead of 273.0K like e.g. the C201. We now read
this value from a suspected file header field.
This commit is contained in:
jaseg 2024-10-31 15:39:09 +01:00
parent 321f829958
commit a51a52291f
1 changed files with 16 additions and 10 deletions
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26
src/infiray_irg.py
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@ -1,4 +1,5 @@
from PIL import Image
import warnings
import numpy as np
import struct
import io
@ -26,14 +27,19 @@ def load(data):
_zero0, _unk1, _zero1, fine_offset, _unk2, jpeg_length,\
y_res_2, x_res_2, _unk3, = struct.unpack('<HIHHHHHHHIHHI', header[2:34])
_zero_celsius0, _zero_celsius1, *rest, high_gain_mode_flag = struct.unpack('<11I', header[34:78])
fine_temp_offset1, fine_temp_offset2, *rest, high_gain_mode_flag = struct.unpack('<11I', header[34:78])
import textwrap
print(textwrap.dedent(f'''
{_unk0=}, {coarse_section_length=}, {y_res=}, {x_res=},
{_zero0=}, {_unk1=}, {_zero1=}, {fine_offset=}, {_unk2=}, {jpeg_length=},
{y_res_2=}, {x_res_2=}, {_unk3=}
{_zero_celsius0=} {_zero_celsius1=} {rest=}, {high_gain_mode_flag=}'''))
if fine_temp_offset1 != fine_temp_offset2:
warnings.warn(f'File lists two different zero offsets for the fine image data {fine_temp_offset1} and {fine_temp_offset2}. Resulting radiometric data might be offset. Please report this with an example file to code@jaseg.de.')
fine_temp_offset = fine_temp_offset1 / 10000
# import textwrap
# print(textwrap.dedent(f'''
# {_unk0=}, {coarse_section_length=}, {y_res=}, {x_res=},
# {_zero0=}, {_unk1=}, {_zero1=}, {fine_offset=}, {_unk2=}, {jpeg_length=},
# {y_res_2=}, {x_res_2=}, {_unk3=}
# {fine_temp_offset1=} {fine_temp_offset1=} {rest=}, {high_gain_mode_flag=}'''))
if (x_res, y_res) != (x_res_2, y_res_2) and model != 'p200':
raise ValueError(f'Resolution mismatch in header: {x_res}*{y_res} != {x_res_2}*{y_res_2}')
@ -47,7 +53,7 @@ def load(data):
coarse_img = np.frombuffer(consume(coarse_section_length), dtype=np.uint8).reshape((y_res, x_res))
# 1/16th Kelvin steps
fine_img = np.frombuffer(consume(x_res*y_res*2), dtype=np.uint16).reshape((y_res, x_res))
fine_img = (fine_img / 16) - 273
fine_img = (fine_img / 16) - fine_temp_offset
vis_jpg = Image.open(io.BytesIO(consume(jpeg_length)))
@ -57,7 +63,7 @@ def load(data):
coarse_img = np.frombuffer(consume(coarse_section_length), dtype=np.uint8).reshape((y_res, x_res))
# 0.1 Kelvin steps
fine_img = np.frombuffer(consume(x_res*y_res*2), dtype=np.uint16).reshape((y_res, x_res))
fine_img = fine_img / 10 - 273
fine_img = fine_img / 10 - fine_temp_offset
vis_jpg = Image.open(io.BytesIO(data))
@ -65,7 +71,7 @@ def load(data):
header += consume(128)
coarse_img = np.frombuffer(consume(coarse_section_length), dtype=np.uint8).reshape((y_res, x_res))
fine_img = np.frombuffer(consume(x_res*y_res*2), dtype=np.uint16).reshape((y_res, x_res))
fine_img = fine_img / 10 - 273
fine_img = fine_img / 10 - fine_temp_offset
# In my example file, data now contains the JSON '{"roi":[]}' and no JPG. We ignore that.
vis_jpg = None