1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
|
# SPDX-FileCopyrightText: Copyright 2021-2023 Arm Limited and/or its affiliates <open-source-office@arm.com>
# 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.Resampling.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)
|
