def deal_with_ias():
"""
# 封装ias
:param algo_image: 接收传入的镜像名称:image_name,
:return:
"""
res_datas = request.values
port = res_datas.get('port')
port = int(port)
image_name = res_datas.get('image_name')
# 获取到容器id
cmd = run_sdk_config_GPU + f"-p {port}:80 {image_name}"
status, res = sdk_subprocess(cmd)
print(res, "res")
if status:
contain_id = res[:12]
elif "port is already" in res:
return jsonify(errno=RET.DATAERR, errmsg="端口被占用请重新输入")
else:
return jsonify(errno=RET.DATAERR, errmsg="输入镜像名称有误请重新确认之后输入")
# 获取OpenCV版本
url = request_host + "/api/v1.0/algo_sdk/opencv_message"
data = {"image_name": image_name}
OpenCv = requests.post(url, data=data).json().get("OpenCv")
# 判断命令上传封装的ias包p
if OpenCv == 3.4:
cmd = f"cp {path}/sdk_package/ias/ias_3.4.tar.gz /tmp/ljx;tar -xvf /tmp/ljx/ias_3.4.tar.gz -C /tmp/ljx"
status, _ = sdk_subprocess(cmd)
if not status:
return jsonify(errno=RET.DATAERR, errmsg="封装失败,请联系管理员")
else:
cmd = f"cp {path}/sdk_package/ias/ias_4.1.tar.gz /tmp/ljx;tar -xvf /tmp/ljx/ias_4.1.tar.gz -C /tmp/ljx"
status, _ = sdk_subprocess(cmd)
if not status:
return jsonify(errno=RET.DATAERR, errmsg="封装失败,请联系管理员")
# 上传成功之后解压 安装
ias_install = f"docker exec {contain_id} bash /tmp/give_license.sh &"
subprocess.Popen(ias_install, shell=True)
return jsonify(errno=RET.OK, errmsg='封装IAS成功,可以直接调用IAS')
def deal_with_vas():
"""
# 封装vas
:param algo_image: 接收传入的镜像名称:image_name,
:return:
"""
res_datas = request.values
image_name = res_datas.get('image_name')
# 获取OpenCV版本
url = request_host + "/api/v1.0/algo_sdk/opencv_message"
data = {"image_name": image_name}
OpenCv = requests.post(url, data=data).json().get("OpenCv")
# 判断命令上传封装的ias包p
if OpenCv == 3.4:
docker_vas = f"docker build -t {image_name}_test --build-arg IMAGE_NAME={image_name} -f {opencv34_dir} ."
else:
docker_vas = f"docker build -t {image_name}_test --build-arg IMAGE_NAME={image_name} -f {opencv41_dir} ."
status, res_docker_vas = sdk_subprocess(docker_vas)
if not status:
return jsonify(errno=RET.DATAERR,
errmsg=f"封装失败,请联系管理员, {res_docker_vas}")
# 上传成功之后解压 安装
# 获取到容器id
cmd = run_sdk_config_GPU + f"-p {image_name}_test"
status, contain_id = sdk_subprocess(cmd)
os.system(
f"docker cp {path}/sdk_package/vas/authorzation.sh {contain_id}:/usr/local/ev_sdk "
)
os.system(
f"docker exec {contain_id} bash /usr/local/ev_sdk/authorzation.sh &")
cmd = f"docker exec {contain_id} bash -c 'cat /usr/local/vas/vas_data/log/vas.INFO|grep \"ji_init return = 0\"'"
status, res_code = sdk_subprocess(cmd)
if not status:
return jsonify(errno=RET.ALGOVERSIONERR, errmsg=f'封装VAS失败,{res_code}')
if int(res_code[-1]) == 0:
return jsonify(errno=RET.OK, errmsg='封装IAS成功,可以直接调用IAS')
else:
return jsonify(errno=RET.ALGOVERSIONERR, errmsg=f'封装VAS失败,{res_code}')
def run_files(self, rootDir, port, names, iou, args, alert_info, hat):
filenames = iter_files(rootDir)
xmls = filenames["xmls"]
files = filenames["files"]
total_files = len(files)
file_count = 0
path = os.path.dirname(
os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
for xml in xmls:
xml_create(xml, path)
time.sleep(3)
for file in files:
file_count += 1
if hat is not None and hat.endswith("gpu"):
hat = "report_num_hat"
txt_create(file, port, names, args, alert_info, hat)
else:
txt_create(file, port, names, args, alert_info)
process = int(file_count / total_files * 100)
self.update_state(state='PROGRESS',
meta={
'current': file_count,
'total': total_files,
'status': process
})
main = os.path.join(path, "utils/sdk_precision/main.py")
if iou is None:
cmd = f"python3 {main}"
else:
cmd = f"python3 {main} -t {iou}"
os.system(cmd)
file_res = os.path.join(path, f"utils/sdk_precision/output/output.txt")
with open(file_res, 'r') as f:
res = f.read().splitlines()
res = str(res).replace("'',", "\n")
clear_dirs()
contain_stop = "docker ps |grep %s|awk '{print $1}'|xargs docker stop" % port
status, _ = sdk_subprocess(contain_stop)
print(rootDir, "rootDir")
os.system(f"rm -rf {rootDir}")
return {
'current': 100,
'total': 100,
'status': 'Task completed!',
"result": res
}
def deal_with_files_data(self, file_name, files_dir, port, file_suffix,
tag_suffix, tag_kinds):
# 解压
os.system(f"unzip {file_name} -d {files_dir}")
# 删除文件
os.system(f"rm -f {file_name}")
total_files = iter_files(files_dir)
# 封装ias 启动算法
url = request_host + "/api/v1.0/algo_sdk/package_ias"
data = {
"port":
port,
"image_name":
"ccr.ccs.tencentyun.com/source/dev_helmet_kww_cpu_sdk3.0_modc_uni_lic1b:v1.1.1"
}
res = requests.post(url, data=data).json().get("errno")
if res != "0":
return jsonify(error=RET.ALGOVERSIONERR, errmsg="封装ias失败")
# 遍历
# 验证文件和标签数据是否一致 判断文集和标签是否以指定文件后缀统一格式
files_tag_dir = total_files["files_tag_dir"]
files = total_files["files"]
for file_tag_dir, file in zip(files_tag_dir, files):
file_tag = file_tag_dir.split("/")[-1]
# 判断文件和标注文件命名是否匹配
if file_tag.split(".")[0] != file.split(".")[0]:
error_files_list["filename_not_match"].append(file)
# 判断是否是以否以指定后缀命名
if not file.endswith(file_suffix):
error_files_list["image"].append(file)
if not file_tag.endswith(tag_suffix):
error_files_list["tag"].append(file_tag)
# 处理xml标签中存在小数点, 更正小数点为正数, 以及判断是否存在多余的标签, 并且删除掉
if file_tag.endswith("xml"):
get_xml_res(file_tag_dir, tag_kinds)
# 判断xml类型是不是ascii
with open(file_tag_dir, 'rb') as f:
data = f.read()
if chardet.detect(data).get("encoding") != 'ascii':
error_files_list["tag_file_not_ascii"].append(file_tag)
# 判断命名是否存在中文
pattern = re.compile(u"[\u4e00-\u9fa5]+")
result = re.findall(pattern, file)
if result:
error_files_list["file_contains_chinese"].append(file)
self.update_state(state='PROGRESS',
meta={
'current': 4,
'total': 10,
'status': 40
})
# 通过算法运行判断图片是否能正常运行
files = total_files["files_dir"]
url = request_host_without_port + ":" + str(port) + "/api/analysisImage"
time.sleep(5)
for file in files:
filename = file.split("/")[-1]
data = {'image': (filename, open(file, 'rb'))}
try:
requests.post(url, files=data)
except Exception as e:
error_files_list["file_cant_open"].append(filename)
self.update_state(state='PROGRESS',
meta={
'current': 9,
'total': 10,
'status': 90
})
# 打包下载结果
with open(os.path.join(files_dir, "res.txt"), 'a') as f:
f.write(str(error_files_list))
os.system(f"cd {files_dir};tar -cvf result.tar *")
result_files = f"{files_dir}/result.tar"
cmd = "docker ps|grep %s|awk '{print $1}'" % port
status, container_id = sdk_subprocess(cmd)
return {
'current': 100,
'total': 100,
'status': 'Task completed!',
'result': result_files,
"container_id": container_id,
"files_dir": files_dir
}
def sdk_opencv_message():
"""
用于获取sdk的opencv版本等相关信息
:return:
"""
res_datas = request.values
image_name = res_datas.get('image_name')
sdk_version = 3
# 获取到容器id
cmd_run_sdk = run_sdk_config_GPU + f"{image_name}"
status, res = sdk_subprocess(cmd_run_sdk)
if status:
contain_id = res[:12]
else:
return jsonify(errno=RET.DATAERR, errmsg="算法镜像不存在或者算法镜像有误,请确认之后再输入!")
sdk_message = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/authorization/privateKey.pem'"
res_p = subprocess.Popen(sdk_message,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
if "No such file or directory" not in stdout.decode('utf-8'):
errmsg = "(1):算法SDK版本为3.0系列 配置路径为:/usr/local/ev_sdk/config/algo_config.json \n"
else:
sdk_version = 2
errmsg = "(1):算法SDK版本为2.0系列 配置路径为:/usr/local/ev_sdk/model/algo_config.json \n"
auth_message = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/3rd/license/lib/pkgconfig/ji_license.pc |grep -i version'"
res_p = subprocess.Popen(auth_message,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
if not stdout.decode('utf-8').startswith("cat"):
errmsg += "(2):当前默认应该使用最新的版本库20.1.3, 当前算法授权库版本为" + str(
stdout.decode('utf-8'))
else:
errmsg += "(2):获取授权信息失败, 授权库不是最新的20.1.3" + "\n"
opencv_message = f"docker exec -it {contain_id} bash ldd /usr/local/ev_sdk/lib/libji.so |egrep 'libopencv_core.so.4'"
res_p = subprocess.Popen(opencv_message,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
if stdout.decode('utf-8') is not '':
# 公私钥 配置文件 查看
privateKey = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/authorization/privateKey.pem'"
res_p = subprocess.Popen(privateKey,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
privateKey = stdout.decode('utf-8')
algo_config = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/config/algo_config.json'"
res_p = subprocess.Popen(algo_config,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
algo_config = stdout.decode('utf-8')
errmsg += '(3):当前OpenCV版本为:3.4, vas安装包:vas_v4.3_cv3.4.tar.gz, ias安装包:ias_v4.90_cv3.4.tar.gz'
OpenCv = 3.4
if sdk_version == 2:
privateKey = "不支持2.0系列算法"
algo_config = "不支持2.0系列算法"
stop = f"docker stop {contain_id}"
subprocess.Popen(stop,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
return jsonify(errno=RET.OK,
errmsg=errmsg,
privateKey=privateKey,
algo_config=algo_config,
OpenCv=OpenCv)
else:
privateKey = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/authorization/privateKey.pem'"
res_p = subprocess.Popen(privateKey,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
privateKey = stdout.decode('utf-8')
algo_config = f"docker exec -it {contain_id} bash -c 'cat /usr/local/ev_sdk/config/algo_config.json'"
res_p = subprocess.Popen(algo_config,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
stdout, stderr = res_p.communicate()
algo_config = stdout.decode('utf-8')
if sdk_version == 2:
privateKey = "不支持2.0系列算法"
algo_config = "不支持2.0系列算法"
errmsg += '(3):当前OpenCV版本为:4.1, vas安装包:vas_v4.3_cv4.1.tar.gz, ias安装包:ias_v4.74_cv4.1.tar.gz '
OpenCv = 4.1
stop = f"docker stop {contain_id}"
subprocess.Popen(stop,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
return jsonify(errno=RET.OK,
errmsg=errmsg,
privateKey=privateKey,
algo_config=algo_config,
OpenCv=OpenCv)