update py and md
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chen
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@@ -3,43 +3,11 @@
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img2bin能够生成模型推理所需的输入数据，以.bin格式保存。
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有两类数据，一类是图片数据，另一类是模型需要的第二个输入数据，如fasterrcnn的第二个输入是图片的shape信息。
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## 环境准备
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## 前提条件
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执行此脚本需要安装python3的opencv，**如已安装可跳过环境准备**。
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脚本可在Centos和Ubuntu环境下使用，需提前安装python3和pip3。
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1. 在root用户下更换源。
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```
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vim /etc/apt/sources.list
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```
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把原有的源更换为国内可用的源，arm源可参考 https://bbs.huaweicloud.com/forum/thread-61366-1-1.html 。
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源更新后，执行以下命令更新软件列表。
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```
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apt-get update
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```
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2. 安装python3的依赖。
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```
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apt-get install python3-setuptools python3-dev build-essential python3-pip
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```
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```
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pip3 install enum34==1.1.6 future==0.17.1 funcsigs==1.0.2 unique protobuf numpy
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```
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>**说明：**
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>
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> pip3 install安装有报错“SSLError”时，请使用：pip3 install --trusted-host pypi.org --trusted-host files.pythonhosted.org numpy==1.11.2 enum34==1.1.6 future==0.17.1 funcsigs==1.0.2 unique protobuf 安装依赖，表示可信赖的主机解决问题。
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3. 安装opencv。
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```
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pip3 install opencv_python
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```
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如未安装opencv-python，脚本会自动安装。
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## 获取脚本
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@@ -58,11 +26,10 @@ img2bin能够生成模型推理所需的输入数据，以.bin格式保存。
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## 使用方法
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进入脚本所在目录。
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```
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cd $HOME/AscendProjects/tools/img2bin
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cd $HOME/AscendProjects/img2bin
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```
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### 第一类图片：
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- -i后跟**目录**表示转换图片。
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- 脚本会将 -i 后指定的图片目录下的所有图片按参数设置做相应的预处理，并以"文件名.bin"命名保存在-o指定的输出目录下。
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```
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@@ -70,10 +37,10 @@ python3 img2bin.py -i ./images -w 416 -h 416 -f BGR -a NHWC -t uint8 -m [104,117
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```
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### 第二类：
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- -i后跟**文件路径**表示转换第二类数据。
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- 第二类数据，需要新建一个文件，文件模板为test.txt，"input_node"为数据，"shape"为数据的shape信息。
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- 第二类数据，需要新建一个文件，文件模板为test.txt，"input_node"为数据，"shape"为数据的shape信息。
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- 文件模板的后缀必须是“.txt”。
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- 第二类数据只需 -i、-t、-o三个参数。
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- 参数 -i 需要指定文件的路径，-t 需要指定数据类型，-o指定输出目录。
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- 参数 -i 需要指定文件的目录或路径，-t 需要指定数据类型，-o指定输出目录。
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```
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python3 img2bin.py -i ./test.txt -t uint8 -o ./out
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@@ -83,7 +50,7 @@ python3 img2bin.py -i ./test.txt -t uint8 -o ./out
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| 参数名 | 说明 |
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| - | - |
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| -i | 图片的输入目录或第二个输入的文件路径 |
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| -i | 输入目录或路径， <br>**在目录下，不能同时有图片和txt，一次只能转一种数据** |
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| -w | 输出图片宽 |
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| -h | 输出图片高 |
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| -f | 输出图片色彩格式，支持（BGR/RGB/YUV/GRAY） |
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+55
-54
@@ -31,23 +31,28 @@
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# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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# POSSIBILITY OF SUCH DAMAGE.
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# =======================================================================
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#
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import argparse
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import configparser
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import cv2 as cv
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import numpy as np
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import json
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import os
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import re
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import sys
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try:
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import cv2 as cv
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except:
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os.system('pip3 install --trusted-host pypi.org --trusted-host files.pythonhosted.org opencv-python')
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import cv2 as cv
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try:
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import numpy as np
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except:
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os.system('pip3 install --trusted-host pypi.org --trusted-host files.pythonhosted.org numpy')
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import numpy as np
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def get_args():
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parser = argparse.ArgumentParser(
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conflict_handler='resolve',
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description='''eg1: python3 imgtobin.py
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-i ./images -w 416 -h 416 -f BGR -a NCHW -m [104,117,123] -o ./out
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eg2: python3 imgtobin.py -i ./test.txt -t uint8''')
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-i ./images -w 416 -h 416 -f BGR -a NHWC -t uint8 -m [104,117,123] -c [1,1,1] -o ./out
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eg2: python3 imgtobin.py -i ./test.txt -t uint8 -o ./out''')
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parser.add_argument('-i', '--input', required=True, type=str, \
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help='folder of input image or file of other input.')
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parser.add_argument('-w', '--width', type=int, \
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@@ -82,30 +87,19 @@ def check_args(args):
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check_flag = True
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is_dir = True
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if os.path.isdir(args.input):
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#print(args)
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if not os.listdir(args.input):
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eprint('[ERROR] input image path=%r is empty.' % path)
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eprint('[ERROR] input image path=%r is empty.' % args.input)
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check_flag = False
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elif os.path.isfile(args.input):
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is_dir = False
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else:
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eprint('[ERROR] input path=%r does not exist.' % path)
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eprint('[ERROR] input path=%r does not exist.' % args.input)
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check_flag = False
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if args.output_image_format not in ('BGR','RGB', 'YUV', 'GRAY'):
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eprint("ERROR:Convert to %d is not support"%(args.output_image_format))
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check_flag = False
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# if os.path.isfile(args.output_path):
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# eprint('[ERROR] argument output_path should be a folder.')
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# elif not os.path.exists(args.output_path):
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# os.makedirs(args.output_path)
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# if not 16 <= args.model_width <= 4096:
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# eprint('[ERROR] resized image width should between 16 and 4096.')
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# check_flag = False
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# if not 16 <= args.model_height <= 4096:
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# eprint('[ERROR] resized image height should between 16 andd 4096.')
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# check_flag = False
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return check_flag, is_dir
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def convert_img(args, input_img):
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@@ -116,11 +110,11 @@ def convert_img(args, input_img):
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elif args.output_image_format == 'YUV':
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if input_img.shape[0] % 2 == 1:
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if input_img.shape[1] % 2 == 1:
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input_img = cv.resize(input_img, ((input_img.shape[0] + 1), (input_img.shape[1] + 1)))
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input_img = cv.resize(input_img, ((input_img.shape[0] + 1), (input_img.shape[1] + 1)))
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else:
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input_img = cv.resize(input_img, ((input_img.shape[0] + 1), input_img.shape[1]))
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input_img = cv.resize(input_img, ((input_img.shape[0] + 1), input_img.shape[1]))
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elif input_img.shape[1] % 2 == 1:
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input_img = cv.resize(input_img, (input_img.shape[0], input_img.shape[1] + 1))
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input_img = cv.resize(input_img, (input_img.shape[0], input_img.shape[1] + 1))
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converted_input_img = cv.cvtColor(input_img, cv.COLOR_BGR2YUV_I420)
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elif args.output_image_format == 'GRAY':
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converted_input_img = cv.cvtColor(input_img, cv.COLOR_BGR2GRAY)
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@@ -192,43 +186,50 @@ def mkdir_output(args):
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return
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def process(args, file_path):
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if file_path.endswith(".txt"):
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config = configparser.ConfigParser()
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config.read(file_path)
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input_node = json.loads(config['baseconf']['input_node'])
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shape = json.loads(config['baseconf']['shape'])
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input_node_np = np.array(input_node)
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change_type_img_info = change_type(args, input_node_np)
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img_info = np.reshape(change_type_img_info, shape)
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out_path = os.path.join(args.output, os.path.splitext(os.path.split(file_path)[1])[0] + ".bin")
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mkdir_output(args)
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img_info.tofile(out_path)
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else:
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input_img = cv.imread(file_path)
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if args.output_image_format == 'YUV':
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resized_img1 = resize_img(args, input_img)
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converted_img = convert_img(args, resized_img1)
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mean_img = mean(args, converted_img)
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else:
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converted_img = convert_img(args, input_img)
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resized_img = resize_img(args, converted_img)
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mean_img = mean(args, resized_img)
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coefficient_img = coefficient(args, mean_img)
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change_type_img = change_type(args, coefficient_img)
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change_format_img = change_format(args, change_type_img)
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out_path = os.path.join(args.output, os.path.splitext(os.path.split(file_path)[1])[0] + ".bin")
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mkdir_output(args)
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change_format_img.tofile(out_path)
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def main():
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"""main function to receive params them change data to bin.
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"""
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args = get_args()
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ret,is_dir = check_args(args)
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ret, is_dir = check_args(args)
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if ret:
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if is_dir:
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img_names = os.listdir(args.input)
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for img_name in img_names:
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img_path = os.path.join(args.input, img_name)
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input_img = cv.imread(img_path)
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if args.output_image_format == 'YUV':
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resized_img1 = resize_img(args, input_img)
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converted_img = convert_img(args, resized_img1)
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mean_img = mean(args, converted_img)
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else:
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converted_img = convert_img(args, input_img)
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resized_img = resize_img(args, converted_img)
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mean_img = mean(args, resized_img)
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coefficient_img = coefficient(args, mean_img)
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change_type_img = change_type(args, coefficient_img)
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change_format_img = change_format(args, change_type_img)
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out_path = os.path.join(args.output, os.path.splitext(img_name)[0] + ".bin")
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mkdir_output(args)
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change_format_img.tofile(out_path)
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files_name = os.listdir(args.input)
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for file_name in files_name:
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file_path = os.path.join(args.input, file_name)
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process(args, file_path)
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else:
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config = configparser.ConfigParser()
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config.read(args.input)
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input_node = json.loads(config['baseconf']['input_node'])
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shape = json.loads(config['baseconf']['shape'])
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input_node_np = np.array(input_node)
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change_type_img_info = change_type(args, input_node_np)
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img_info = np.reshape(change_type_img_info, shape)
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out_path = os.path.join(args.output, os.path.splitext(args.input)[0] + ".bin")
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mkdir_output(args)
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img_info.tofile(out_path)
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process(args, args.input)
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if __name__ == '__main__':
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main()
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