def auditConfig(self):
for name in self._mandatory_member_name:
if name not in self._mandatory_member:
LOG.logE(
"Error! self.{} must be definded in your subclass.".format(
name),
exit=True)
def exportNCNN(self, img):
if not self.conf.ncnn_param_output_path or not self.conf.ncnn_bin_output_path:
return
if not self.conf.onnx2ncnn:
LOG.logE(
"You must set the onnx2ncnn executable program path in config file. If you want to compile onnx2ncnn tools, reference https://github.com/Tencent/ncnn/wiki/how-to-build#build-for-linux-x86 ",
exit=True)
import onnx
import subprocess
import tempfile
from onnxsim import simplify
if not self.conf.onnx_output_model_path:
f = tempfile.NamedTemporaryFile()
self.conf.onnx_output_model_path = f.name
self.exportONNX(img)
cmd = self.conf.onnx2ncnn + " " + self.conf.onnx_output_model_path + " " + self.conf.ncnn_param_output_path + " " + self.conf.ncnn_bin_output_path
pd = subprocess.Popen(cmd,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
if pd.stderr.read() != b"":
LOG.logE(
pd.stderr.read() +
b". Error occured when export ncnn model. We try to simplify the model first"
)
model_op, check_ok = simplify(self.conf.onnx_output_model_path,
check_n=3,
perform_optimization=True,
skip_fuse_bn=True,
skip_shape_inference=False)
onnx.save(model_op, self.conf.onnx_output_model_path)
if not check_ok:
LOG.logE(
"Maybe something wrong when simplify the model, we can't guarantee generate model is right"
)
else:
LOG.logI("Simplify model succeed")
subprocess.Popen(cmd,
shell=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
if pd.stderr.read() != b"":
LOG.logE(pd.stderr.read() +
b". we can't guarantee generate model is right")
LOG.logI(
"Pytorch model convert to NCNN model succeed, save ncnn param file in {}, save ncnn bin file in {}"
.format(self.conf.ncnn_param_output_path,
self.conf.ncnn_bin_output_path))
def assertInGit(self):
if os.environ.get("disable_git"):
self.branch = "sevice"
return
if self.conf.disable_git:
self.branch = "disable_git"
return
self.branch = getCurrentGitBranch()
if self.branch is None:
LOG.logE(
'According to deepvac standard, you must working in a git repo.',
exit=True)
if len(self.branch) < 6:
LOG.logE(
'According to deepvac standard, your git branch name is too short: {}'
.format(self.branch),
exit=True)
if self.branch.startswith('LTS_'):
return
if self.branch.startswith('PROTO_'):
return
LOG.logE(
'According to deepvac standard, git branch name should start from LTS_ or PROTO_: {}'
.format(self.branch),
exit=True)
def process(self):
label_list = config.label_list
for image_path in self.dataset():
self.getTask(image_path)
self.request.set_content(
HttpContentHelper.toValue({
"tasks": [self.task],
"scenes": [config.scenes]
}))
response = self.clt.do_action_with_exception(self.request)
result = json.loads(response)
if result['code'] != 200:
LOG.logE(
f"got request error! please checkout your AccessKeyId and Secret"
)
continue
if result['data'][0]['code'] != 200:
LOG.logE(
f"got error! [file: {image_path}, msg: {result['data'][0]['msg']}]"
)
continue
pred = result['data'][0]['results'][0]['label']
label = image_path.split('/')[-2]
if label not in label_list:
LOG.logE(f"got error! test file structure not standard")
continue
LOG.logI(
f"got Success! [file: {image_path}, label: {label}, pred: {pred}]"
)
self.report.add(label_list.index(label), label_list.index(pred))
def initValLoader(self):
self.val_loader = None
LOG.logE(
"You must reimplement initTrainLoader() to initialize self.val_loader",
exit=True)
def process(self):
LOG.logE(
"You must reimplement process() to process self.input_output['input']",
exit=True)
def initNetWithCode(self):
self.net = None
LOG.logE(
"You must reimplement initNetWithCode() to initialize self.net",
exit=True)