import fastdeploy as fd
import cv2
import os


def parse_arguments():
    import argparse
    import ast
    parser = argparse.ArgumentParser()
    parser.add_argument(
        "--model", required=True, help="Path of PaddleClas model.")
    parser.add_argument(
        "--image", type=str, required=True, help="Path of test image file.")
    parser.add_argument(
        "--topk", type=int, default=1, help="Return topk results.")
    return parser.parse_args()


def build_option(args):

    option = fd.RuntimeOption()
    option.use_kunlunxin()

    return option


args = parse_arguments()

# 配置runtime，加载模型
runtime_option = build_option(args)

model_file = os.path.join(args.model, "inference.pdmodel")
params_file = os.path.join(args.model, "inference.pdiparams")
config_file = os.path.join(args.model, "inference_cls.yaml")
model = fd.vision.classification.PaddleClasModel(
    model_file, params_file, config_file, runtime_option=runtime_option)

# 预测图片分类结果
im = cv2.imread(args.image)
result = model.predict(im, args.topk)
print(result)