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) for model, match in { 'c201': bytes([0xca, 0xac]), 'other': bytes([0xba, 0xab]), 'p200': bytes([0x04, 0xa0]), }.items(): if (header[:2] + header[-2:]).startswith(match): break else: raise ValueError(f'Header magic not found. Got header: {header[0]:02x} {header[1]:02x}') _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]) 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 (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}') if x_res*y_res != coarse_section_length: raise ValueError('Resolution mismatch in header') if model == 'c201': if header[-2:] != bytes([0xac,0xca]): raise ValueError(f'Header end marker not found. Got header: {header[-2]:02x} {header[-1]:02x}') 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 vis_jpg = Image.open(io.BytesIO(consume(jpeg_length))) elif model == 'other': if header[-2:] != bytes([0xab,0xba]): raise ValueError(f'Header end marker not found. Got header: {header[-2]:02x} {header[-1]:02x}') 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 vis_jpg = Image.open(io.BytesIO(data)) else: 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 # In my example file, data now contains the JSON '{"roi":[]}' and no JPG. We ignore that. vis_jpg = None return coarse_img, fine_img, vis_jpg