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gen_rgb_cpp.py
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gen_rgb_cpp.py
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# 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
import os
import numpy as np
import cv2
from argparse import ArgumentParser
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(os.path.join(os.path.dirname(__file__), '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=os.path.basename(__file__),
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 {os.path.basename(cc_filename)}")
header_template = env.get_template(header_template_file)
hdr = header_template.render(script_name=os.path.basename(__file__),
gen_time=datetime.datetime.now(),
file_name=os.path.basename(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
# ))
#############################################
original_image = np.array(original_image)
resized_image = cv2.resize(
original_image, (ifm_width, ifm_height), interpolation=cv2.INTER_LINEAR
)
# resized_image = cv2.cvtColor(resized_image, cv2.COLOR_BGR2RGB)
resized_image = resized_image.reshape(-1, ifm_width, ifm_height, 3)
#####################################################
# 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 os.path.isdir(args.image_path):
filepaths = sorted(glob.glob(os.path.join(args.image_path, '**/*.*'), recursive=True))
elif os.path.isfile(args.image_path):
filepaths = [args.image_path]
else:
raise OSError("Directory or file does not exist.")
for filepath in filepaths:
filename = os.path.basename(filepath)
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 = os.path.join(args.source_folder_path,
(filename.rsplit(".")[0]).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 = os.path.join(args.header_folder_path, header_filename)
common_cc_filename = "InputFiles.cc"
common_cc_filepath = os.path.join(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)