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#!/usr/bin/env python |
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""" |
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A command-line tool for spliting POV-Ray density file (DF3) |
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to a series of separate images. |
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""" |
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from __future__ import print_function |
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import sys |
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import os |
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import argparse |
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import struct |
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from PIL import Image |
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from df3tools.exceptions import Df3Exception |
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def from_big_endian(bytestring): |
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""" Convert big-endian bytestring to int """ |
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bytestring = bytestring.rjust(4, b'\x00') |
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return struct.unpack(">L", bytestring)[0] |
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def split_by_n(seq, chunk_size): |
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""" Generator splitting a sequence into chunks """ |
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while seq: |
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yield seq[:chunk_size] |
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seq = seq[chunk_size:] |
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def detect_size(df3_file, silent): |
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""" |
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Detect image size and number of layers. |
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:param df3_file: DF3 file descriptor. |
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:param silent: suppress output (info messages, progress etc.) |
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:returns: Tuple with sizes. |
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""" |
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header = df3_file.read(6) |
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sizes = [from_big_endian(v) for v in split_by_n(header, 2)] |
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width, height, num_layers = sizes |
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if not silent: |
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print("Size: %dx%d, %d layers" % (width, height, num_layers)) |
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return (width, height, num_layers) |
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def detect_byte_width(data, num_voxels, silent): |
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""" |
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Detect byte width. |
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:param data: Byte string with DF3 body. |
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:param num_voxels: Number of voxels in file. |
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:param silent: suppress output (info messages, progress etc.) |
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""" |
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byte_width = int(float(len(data)) / num_voxels) |
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if not silent: |
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plural = ' s'[byte_width > 1] |
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print("Voxel resolution: %d byte%s" % (byte_width, plural)) |
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return byte_width |
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def df3split(filename, prefix="layer", img_format='tga', silent=True): |
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""" |
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Split POV-Ray density file (DF3) to a series of separate images. |
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:param filename: path to DF3 file to process |
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:param prefix: output files prefix |
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:param img_format: output files format (tga, png, etc.) |
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:param silent: suppress output (info messages, progress etc.) |
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""" |
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if not os.path.isfile(filename): |
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raise Df3Exception("File not found: " + filename) |
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with open(filename, "rb") as df3_file: |
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width, height, num_layers = detect_size(df3_file, silent) |
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data = df3_file.read() |
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detect_byte_width(data, width * height * num_layers, silent) |
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# parse data and save images |
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for img_num, img_data in enumerate(split_by_n(data, width * height)): |
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layer_num = str(img_num).zfill(len(str(num_layers))) |
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img = Image.new("L", (width, height)) |
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img.putdata(img_data) |
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img.save("%s%s.%s" % (prefix, layer_num, img_format.lower())) |
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percentage = float(img_num + 1) / num_layers * 100 |
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if not silent: |
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sys.stdout.write("Processing data [%.2f%%]\r" % percentage) |
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sys.stdout.flush() |
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if not silent: |
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print("\nDone.") |
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def main(): |
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""" Main script execution """ |
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parser = argparse.ArgumentParser(description=""" |
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Split POV-Ray density file (DF3) to a series of separate images |
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""") |
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parser.add_argument("df3file", help="DF3 filename, including path") |
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parser.add_argument("-t", "--format", type=str, |
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choices=["tga", "png"], |
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default="tga", |
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help="Output files format") |
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parser.add_argument("-p", "--prefix", type=str, |
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default="layer", |
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help="Output files prefix") |
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parser.add_argument("-s", "--silent", help="Suppress output", |
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default=False, action="store_true") |
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args = parser.parse_args() |
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df3split(args.df3file, args.prefix, args.format, args.silent) |
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if __name__ == "__main__": |
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main() |
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a5kin /
df3tools
