44 lines
1.4 KiB
Python
44 lines
1.4 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
from argparse import ArgumentParser
|
|
|
|
import numpy as np
|
|
import requests
|
|
|
|
from mmpretrain.apis import get_model, inference_model
|
|
|
|
|
|
def parse_args():
|
|
parser = ArgumentParser()
|
|
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(
|
|
'--device', default='cuda:0', help='Device used for inference')
|
|
args = parser.parse_args()
|
|
return args
|
|
|
|
|
|
def main(args):
|
|
# Inference single image by native apis.
|
|
model = get_model(args.config, args.checkpoint, device=args.device)
|
|
model_result = inference_model(model, args.img)
|
|
|
|
# Inference single image by torchserve engine.
|
|
url = 'http://' + args.inference_addr + '/predictions/' + args.model_name
|
|
with open(args.img, 'rb') as image:
|
|
response = requests.post(url, image)
|
|
server_result = response.json()
|
|
|
|
assert np.allclose(model_result['pred_score'], server_result['pred_score'])
|
|
print('Test complete, the results of PyTorch and TorchServe are the same.')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
args = parse_args()
|
|
main(args)
|