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dbf68117fa87ab03eac5873f0f36910862346fdf
ascend-tools/img2bin/img2bin.py
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HuaweiAscend dbf68117fa 重命名 imgtobin 为 img2bin
2020-06-22 11:41:28 +08:00

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# !/usr/bin/env python3
# -*- coding: UTF-8 -*-
#
# =======================================================================
#
# Copyright (C) 2018, Hisilicon Technologies Co., Ltd. All Rights Reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1 Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2 Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3 Neither the names of the copyright holders nor the names of the
# contributors may be used to endorse or promote products derived from this
# software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
# =======================================================================
#
import argparse
import configparser
import cv2 as cv
import numpy as np
import json
import os
import re
import sys
def get_args():
parser = argparse.ArgumentParser(
conflict_handler='resolve',
description='''eg1: python3 imgtobin.py
-i ./images -w 416 -h 416 -f BGR -a NCHW -m [104,117,123] -o ./out
eg2: python3 imgtobin.py -i ./test.txt -t uint8''')
parser.add_argument('-i', '--input', required=True, type=str, \
help='folder of input image or file of other input.')
parser.add_argument('-w', '--width', type=int, \
help='resized image width before inference.')
parser.add_argument('-h', '--height', type=int, \
help='resized image height before inference.')
parser.add_argument('-f', '--output_image_format', default='BGR', type=str, \
help='output image format in (BGR/RGB/YUV/GRAY).')
parser.add_argument('-a', '--output_format', default='NCHW', type=str, \
help='output format in (NCHW/NHWC).')
parser.add_argument('-t', '--output_type', required=True, type=str, \
help='output type in (float32/uint8/int32/uint32).')
parser.add_argument('-m', '--mean', default='[0, 0, 0]', \
help='reduce mean for each channel.')
parser.add_argument('-c', '--coefficient', default='[1, 1, 1]', \
help='multiplying coefficients for each channel.')
parser.add_argument('-o', '--output', default='./', \
help='output path.')
return parser.parse_args()
def eprint(*args, **kwargs):
"""print error message to stderr
"""
print(*args, file=sys.stderr, **kwargs)
def check_args(args):
"""check console parameters according to restrictions.
:return: True or False
"""
check_flag = True
is_dir = True
if os.path.isdir(args.input):
#print(args)
if not os.listdir(args.input):
eprint('[ERROR] input image path=%r is empty.' % path)
check_flag = False
elif os.path.isfile(args.input):
is_dir = False
else:
eprint('[ERROR] input path=%r does not exist.' % path)
check_flag = False
if args.output_image_format not in ('BGR','RGB', 'YUV', 'GRAY'):
eprint("ERROR:Convert to %d is not support"%(args.output_image_format))
check_flag = False
# if os.path.isfile(args.output_path):
# eprint('[ERROR] argument output_path should be a folder.')
# elif not os.path.exists(args.output_path):
# os.makedirs(args.output_path)
# if not 16 <= args.model_width <= 4096:
# eprint('[ERROR] resized image width should between 16 and 4096.')
# check_flag = False
# if not 16 <= args.model_height <= 4096:
# eprint('[ERROR] resized image height should between 16 andd 4096.')
# check_flag = False
return check_flag, is_dir
def convert_img(args, input_img):
if args.output_image_format == 'BGR':
converted_input_img = input_img
elif args.output_image_format == 'RGB':
converted_input_img = cv.cvtColor(input_img, cv.COLOR_BGR2RGB)
elif args.output_image_format == 'YUV':
if input_img.shape[0] % 2 == 1:
if input_img.shape[1] % 2 == 1:
input_img = cv.resize(input_img, ((input_img.shape[0] + 1), (input_img.shape[1] + 1)))
else:
input_img = cv.resize(input_img, ((input_img.shape[0] + 1), input_img.shape[1]))
elif input_img.shape[1] % 2 == 1:
input_img = cv.resize(input_img, (input_img.shape[0], input_img.shape[1] + 1))
converted_input_img = cv.cvtColor(input_img, cv.COLOR_BGR2YUV_I420)
elif args.output_image_format == 'GRAY':
converted_input_img = cv.cvtColor(input_img, cv.COLOR_BGR2GRAY)
return converted_input_img
def resize_img(args, input_img):
resized_img = cv.resize(input_img, (args.width, args.height))
return resized_img
def change_type(args, input_img):
if args.output_type == 'float32':
change_type_img = input_img.astype(np.float32)
elif args.output_type == 'int32':
change_type_img = input_img.astype(np.int32)
elif args.output_type == 'uint32':
change_type_img = input_img.astype(np.uint32)
else:
change_type_img = input_img.astype(np.uint8)
return change_type_img
def mean(args, input_img):
if isinstance (args.mean, str):
args.mean = json.loads(args.mean)
input_img = input_img.astype(np.float32)
if args.output_image_format == 'GRAY':
input_img[:, :] -= args.mean[0]
elif args.output_image_format in ('BGR', 'RGB'):
input_img[:, :, 0] -= args.mean[0]
input_img[:, :, 1] -= args.mean[1]
input_img[:, :, 2] -= args.mean[2]
else:
input_img[: int(args.width / 1.5), :] -= args.mean[0]
input_img[int(args.width / 1.5) :, :: 2] -= args.mean[1]
input_img[int(args.width / 1.5) :, 1: 2] -= args.mean[2]
return input_img
def coefficient(args, input_img):
if isinstance (args.coefficient, str):
args.coefficient = json.loads(args.coefficient)
input_img = input_img.astype(np.float32)
if args.output_image_format == 'GRAY':
input_img[:, :] *= args.coefficient[0]
elif args.output_image_format in ('BGR', 'RGB'):
input_img[:, :, 0] *= args.coefficient[0]
input_img[:, :, 1] *= args.coefficient[1]
input_img[:, :, 2] *= args.coefficient[2]
else:
input_img[: int(args.width / 1.5), :] *= args.coefficient[0]
input_img[int(args.width / 1.5) :, :: 2] *= args.coefficient[1]
input_img[int(args.width / 1.5) :, 1: 2] *= args.coefficient[2]
return input_img
def change_format(args, input_img):
if args.output_format == 'NCHW':
if args.output_image_format in ('RGB', 'BGR'):
change_format_img = input_img.transpose(2,0,1).copy()
return change_format_img
return input_img
def mkdir_output(args):
if not os.path.exists(args.output):
os.makedirs(args.output)
return
def main():
"""main function to receive params them change data to bin.
"""
args = get_args()
ret,is_dir = check_args(args)
if ret:
if is_dir:
img_names = os.listdir(args.input)
for img_name in img_names:
img_path = os.path.join(args.input, img_name)
input_img = cv.imread(img_path)
if args.output_image_format == 'YUV':
resized_img1 = resize_img(args, input_img)
converted_img = convert_img(args, resized_img1)
mean_img = mean(args, converted_img)
else:
converted_img = convert_img(args, input_img)
resized_img = resize_img(args, converted_img)
mean_img = mean(args, resized_img)
coefficient_img = coefficient(args, mean_img)
change_type_img = change_type(args, coefficient_img)
change_format_img = change_format(args, change_type_img)
out_path = os.path.join(args.output, os.path.splitext(img_name)[0] + ".bin")
mkdir_output(args)
change_format_img.tofile(out_path)
else:
config = configparser.ConfigParser()
config.read(args.input)
input_node = json.loads(config['baseconf']['input_node'])
shape = json.loads(config['baseconf']['shape'])
input_node_np = np.array(input_node)
change_type_img_info = change_type(args, input_node_np)
img_info = np.reshape(change_type_img_info, shape)
out_path = os.path.join(args.output, os.path.splitext(args.input)[0] + ".bin")
mkdir_output(args)
img_info.tofile(out_path)
if __name__ == '__main__':
main()
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