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# Copyright (c) OpenMMLab. All rights reserved.
from argparse import ArgumentParser
from io import BytesIO
import matplotlib.pyplot as plt
import mmcv
import requests
from mmseg.apis import inference_model, init_model
def parse_args():
parser = ArgumentParser(
description='Compare result of torchserve and pytorch,'
'and visualize them.')
parser.add_argument('img', help='Image file')
parser.add_argument('config', help='Config file')
parser.add_argument('checkpoint', help='Checkpoint file')
parser.add_argument('model_name', help='The model name in the server')
parser.add_argument(
'--inference-addr',
default='127.0.0.1:8080',
help='Address and port of the inference server')
parser.add_argument(
'--result-image',
type=str,
default=None,
help='save server output in result-image')
parser.add_argument(
'--device', default='cuda:0', help='Device used for inference')
args = parser.parse_args()
return args
def main(args):
url = 'http://' + args.inference_addr + '/predictions/' + args.model_name
with open(args.img, 'rb') as image:
tmp_res = requests.post(url, image)
content = tmp_res.content
if args.result_image:
with open(args.result_image, 'wb') as out_image:
out_image.write(content)
plt.imshow(mmcv.imread(args.result_image, 'grayscale'))
plt.show()
else:
plt.imshow(plt.imread(BytesIO(content)))
plt.show()
model = init_model(args.config, args.checkpoint, args.device)
image = mmcv.imread(args.img)
result = inference_model(model, image)
plt.imshow(result[0])
plt.show()
if __name__ == '__main__':
args = parse_args()
main(args)
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