# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import sys
import numpy as np
from paddle_serving_client import Client
from paddle_serving_app.reader import *
import cv2
preprocess = Sequential([
    File2Image(), BGR2RGB(), Resize(
        (608, 608), interpolation=cv2.INTER_LINEAR), Div(255.0), Transpose(
            (2, 0, 1))
])

postprocess = RCNNPostprocess(sys.argv[1], "output", [608, 608])
client = Client()

client.load_client_config("serving_client/serving_client_conf.prototxt")
client.connect(['127.0.0.1:9393'])

im = preprocess(sys.argv[2])
fetch_map = client.predict(
    feed={
        "image": im,
        "im_shape": np.array(list(im.shape[1:])).reshape(-1),
        "scale_factor": np.array([1.0, 1.0]).reshape(-1),
    },
    fetch=["multiclass_nms3_0.tmp_0"],
    batch=False)
print(fetch_map)
fetch_map["image"] = sys.argv[2]
postprocess(fetch_map)
