def handle_cli(self, args, func):
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True)
parser.add_argument("-o",
"--output",
default="str",
choices=["str", "json"])
parsed_args = parser.parse_args(args)
file_path = parsed_args.input
verify_image_format_or_raise(file_path, self.accept_image_formats)
if not os.path.isabs(file_path):
file_path = os.path.abspath(file_path)
image_array = self.fastai_vision.open_image(
fn=file_path,
convert_mode=self.convert_mode,
div=self.div,
after_open=self.after_open,
cls=self.cls or self.fastai_vision.Image,
)
result = func(image_array)
if parsed_args.output == "json":
result = api_func_result_to_json(result)
else:
result = str(result)
print(result)
def handle_cli(self, args, func):
parser = argparse.ArgumentParser()
parser.add_argument("--input", required=True)
parser.add_argument("-o",
"--output",
default="str",
choices=["str", "json", "yaml"])
parsed_args = parser.parse_args(args)
file_path = parsed_args.input
verify_image_format_or_raise(file_path, self.accept_image_formats)
if not os.path.isabs(file_path):
file_path = os.path.abspath(file_path)
image_array = open_image(
fn=file_path,
convert_mode=self.convert_mode,
div=self.div,
after_open=self.after_open,
cls=self.cls or Image,
)
result = func(image_array)
result = get_output_str(result, output_format=parsed_args.output)
print(result)
def handle_request(self, request, func):
if request.method != "POST":
return Response(response="Only accept POST request", status=400)
input_streams = []
for filename in self.input_names:
file = request.files.get(filename)
if file is not None:
file_name = secure_filename(file.filename)
verify_image_format_or_raise(file_name,
self.accept_image_formats)
input_streams.append(BytesIO(file.read()))
if len(input_streams) == 0:
data = request.get_data()
if data:
input_streams = (data, )
else:
raise ValueError(
"BentoML#ImageHandler unexpected HTTP request: %s" %
request)
input_data = []
for input_stream in input_streams:
data = self.imread(input_stream, pilmode=self.convert_mode)
if self.after_open:
data = self.after_open(data)
data = self.fastai_vision.pil2tensor(data, np.float32)
if self.div:
data = data.div_(255)
if self.cls:
data = self.cls(data)
else:
data = self.fastai_vision.Image(data)
input_data.append(data)
result = func(*input_data)
result = get_output_str(result, request.headers.get("output", "json"))
return Response(response=result,
status=200,
mimetype="application/json")
