predict.py

# Copyright (c) 2022 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 os
import sys
import numpy as np
import math
import glob
import paddle
import cv2

parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
sys.path.insert(0, parent_path)

from ppcv.engine.pipeline import Pipeline
from ppcv.utils.logger import setup_logger
from ppcv.core.config import ArgsParser


def argsparser():
    parser = ArgsParser()

    parser.add_argument(
        "--config",
        type=str,
        default=None,
        help=("Path of configure"),
        required=True)
    parser.add_argument(
        "--input",
        type=str,
        default=None,
        help="Path of input, suport image file, image directory and video file.",
        required=True)
    parser.add_argument(
        "--output_dir",
        type=str,
        default="output",
        help="Directory of output visualization files.")
    parser.add_argument(
        "--run_mode",
        type=str,
        default='paddle',
        help="mode of running(paddle/trt_fp32/trt_fp16/trt_int8/mkldnn/mkldnn_bf16)"
    )
    parser.add_argument(
        "--device",
        type=str,
        default='CPU',
        help="Choose the device you want to run, it can be: CPU/GPU/XPU, default is CPU."
    )
    return parser


if __name__ == '__main__':
    parser = argsparser()
    FLAGS = parser.parse_args()
    input = os.path.abspath(FLAGS.input)
    pipeline = Pipeline(FLAGS)
    result = pipeline.run(input)