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from PIL import Image
import numpy as np
import struct
import io
def load(data):
def consume(n):
nonlocal data
out, data = data[:n], data[n:]
if len(out) < n:
raise ValueError(f'File is truncated, tried to read {n} bytes, but only {len(out)} bytes remain.')
return out
header = consume(128)
if header[:2] not in [
bytes([0xca, 0xac]),
bytes([0xba, 0xab])
] or header[-2:] != bytes([0xac, 0xca]):
raise ValueError('Header magic not found.')
_unk0, coarse_section_length, y_res, x_res,\
_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])
if (x_res, y_res) != (x_res_2, y_res_2):
raise ValueError(f'Resolution mismatch in header: {x_res}*{y_res} != {x_res_2}*{y_res_2}')
if x_res*y_res != coarse_section_length:
raise ValueError('Resolution mismatch in header')
coarse_img = np.frombuffer(consume(coarse_section_length), dtype=np.uint8).reshape((y_res, x_res))
if header[:2] == bytes([0xca, 0xac]):
# 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
vis_jpg = Image.open(io.BytesIO(consume(jpeg_length)))
else: # 0xbaac variant
# 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
vis_jpg = Image.open(io.BytesIO(data))
return coarse_img, fine_img, vis_jpg
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