Bmp To Jc5 Converter Verified Apr 2026

def to_jc5(width, height, channels, pixels, out_path, grayscale=False): if grayscale and channels==3: out_pixels = bytearray(width*height) for i in range(width*height): r = pixels[i*3] g = pixels[i*3+1] b = pixels[i*3+2] y = int(round(0.299*r + 0.587*g + 0.114*b)) out_pixels[i] = y channels_out = 1 elif channels==3 and not grayscale: out_pixels = bytes(pixels) channels_out = 3 elif channels==1: out_pixels = bytes(pixels) channels_out = 1 else: raise ValueError('Unhandled channel conversion')

Overview This document provides a verified, practical implementation plan and reference code to convert BMP image files to JC5 format (a hypothetical/custom binary image format named “JC5”). It covers spec assumptions, exact conversion steps, validation checks, a minimal reference implementation in Python, and test vectors for verification. bmp to jc5 converter verified

header = bytearray(16) header[0:4] = b'JC5\x00' header[4:8] = struct.pack('<I', width) header[8:12] = struct.pack('<I', height) header[12] = channels_out header[13] = 8 if channels_out==1 else 24 header[14:16] = b'\x00\x00' with open(out_path, 'wb') as f: f.write(header) f.write(out_pixels) # verification expected_len = 16 + width*height*channels_out actual_len = 16 + len(out_pixels) if expected_len != actual_len: raise RuntimeError('Size mismatch') h = hashlib.sha256() with open(out_path, 'rb') as f: h.update(f.read()) return h.hexdigest() exact conversion steps

def load_bmp(path): with open(path, 'rb') as f: data = f.read() if data[0:2] != b'BM': raise ValueError('Not a BMP') pixel_offset = read_u32_le(data, 10) dib_size = read_u32_le(data, 14) width = read_u32_le(data, 18) height_signed = struct.unpack_from('<i', data, 22)[0] height = abs(height_signed) bpp = read_u16_le(data, 28) top_down = (height_signed < 0) # Only handle common cases: 24-bit BGR or 8-bit paletted if bpp == 24: row_bytes = ((width * 3 + 3) // 4) * 4 pixels = [] for row in range(height): bmp_row_idx = row if top_down else (height - 1 - row) start = pixel_offset + bmp_row_idx * row_bytes rowdata = data[start:start+width*3] # BMP stores B,G,R for x in range(width): b,g,r = rowdata[x*3:(x+1)*3] pixels.extend([r,g,b]) return width, height, 3, pixels elif bpp == 8: # palette after DIB header (256 * 4 bytes) pal_offset = 14 + dib_size palette = [] entries = 256 for i in range(entries): off = pal_offset + i*4 if off+4 > len(data): break b,g,r,_ = data[off:off+4] palette.append((r,g,b)) row_bytes = ((width + 3)//4)*4 pixels = [] for row in range(height): bmp_row_idx = row if top_down else (height - 1 - row) start = pixel_offset + bmp_row_idx * row_bytes rowdata = data[start:start+width] for x in range(width): idx = rowdata[x] r,g,b = palette[idx] pixels.extend([r,g,b]) return width, height, 3, pixels else: raise ValueError(f'Unsupported BMP bpp: bpp') a minimal reference implementation in Python