# Copyright (c) 2021 Arm Limited. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Utility script to convert a set of RGB images in a given location into corresponding cpp files and a single hpp file referencing the vectors from the cpp files. """ import datetime import glob import math from pathlib import Path from argparse import ArgumentParser import numpy as np from PIL import Image, UnidentifiedImageError from jinja2 import Environment, FileSystemLoader parser = ArgumentParser() parser.add_argument("--image_path", type=str, help="path to images folder or image file to convert.") parser.add_argument("--source_folder_path", type=str, help="path to source folder to be generated.") parser.add_argument("--header_folder_path", type=str, help="path to header folder to be generated.") parser.add_argument("--image_size", type=int, nargs=2, help="Size (width and height) of the converted images.") parser.add_argument("--license_template", type=str, help="Header template file", default="header_template.txt") args = parser.parse_args() env = Environment(loader=FileSystemLoader(Path(__file__).parent / 'templates'), trim_blocks=True, lstrip_blocks=True) def write_hpp_file(header_file_path, cc_file_path, header_template_file, num_images, image_filenames, image_array_names, image_size): print(f"++ Generating {header_file_path}") header_template = env.get_template(header_template_file) hdr = header_template.render(script_name=Path(__file__).name, gen_time=datetime.datetime.now(), year=datetime.datetime.now().year) env.get_template('Images.hpp.template').stream(common_template_header=hdr, imgs_count=num_images, img_size=str(image_size[0] * image_size[1] * 3), var_names=image_array_names) \ .dump(str(header_file_path)) env.get_template('Images.cc.template').stream(common_template_header=hdr, var_names=image_array_names, img_names=image_filenames) \ .dump(str(cc_file_path)) def write_individual_img_cc_file(image_filename, cc_filename, header_template_file, original_image, image_size, array_name): print(f"++ Converting {image_filename} to {cc_filename.name}") header_template = env.get_template(header_template_file) hdr = header_template.render(script_name=Path(__file__).name, gen_time=datetime.datetime.now(), file_name=image_filename, year=datetime.datetime.now().year) # IFM size ifm_width = image_size[0] ifm_height = image_size[1] # Aspect ratio resize scale_ratio = (float)(max(ifm_width, ifm_height)) / (float)(min(original_image.size[0], original_image.size[1])) resized_width = (int)(original_image.size[0] * scale_ratio) resized_height = (int)(original_image.size[1] * scale_ratio) resized_image = original_image.resize([resized_width,resized_height], Image.BILINEAR) # Crop the center of the image resized_image = resized_image.crop(( (resized_width - ifm_width) / 2, # left (resized_height - ifm_height) / 2, # top (resized_width + ifm_width) / 2, # right (resized_height + ifm_height) / 2 # bottom )) # Convert the image and write it to the cc file rgb_data = np.array(resized_image, dtype=np.uint8).flatten() hex_line_generator = (', '.join(map(hex, sub_arr)) for sub_arr in np.array_split(rgb_data, math.ceil(len(rgb_data) / 20))) env.get_template('image.cc.template').stream(common_template_header=hdr, var_name=array_name, img_data=hex_line_generator) \ .dump(str(cc_filename)) def main(args): # Keep the count of the images converted image_idx = 0 image_filenames = [] image_array_names = [] if Path(args.image_path).is_dir(): filepaths = sorted(glob.glob(str(Path(args.image_path) / '**/*.*'), recursive=True)) elif Path(args.image_path).is_file(): filepaths = [args.image_path] else: raise OSError("Directory or file does not exist.") for filepath in filepaths: filename = Path(filepath).name try: original_image = Image.open(filepath).convert("RGB") except UnidentifiedImageError: print(f"-- Skipping file {filepath} due to unsupported image format.") continue image_filenames.append(filename) # Save the cc file cc_filename = Path(args.source_folder_path) / (Path(filename).stem.replace(" ", "_") + ".cc") array_name = "im" + str(image_idx) image_array_names.append(array_name) write_individual_img_cc_file(filename, cc_filename, args.license_template, original_image, args.image_size, array_name) # Increment image index image_idx = image_idx + 1 header_filename = "InputFiles.hpp" header_filepath = Path(args.header_folder_path) / header_filename common_cc_filename = "InputFiles.cc" common_cc_filepath = Path(args.source_folder_path) / common_cc_filename if len(image_filenames) > 0: write_hpp_file(header_filepath, common_cc_filepath, args.license_template, image_idx, image_filenames, image_array_names, args.image_size) else: raise FileNotFoundError("No valid images found.") if __name__ == '__main__': main(args)