PaddleX/libs/paddlex-hpi/tests/models/test_image_unwarping.py

# Copyright (c) 2024 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 numpy as np
from paddlex_hpi.models import WarpPredictor
from tests.models.base import BaseTestPredictor

from paddlex.inference.results import DocTrResult

MODEL_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_model.zip"
INPUT_DATA_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_input.jpg"
EXPECTED_RESULT_URL = "https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/deploy/paddlex_hpi/tests/models/warp_result.json"


class TestWarpPredictor(BaseTestPredictor):
    @property
    def model_url(self):
        return MODEL_URL

    @property
    def input_data_url(self):
        return INPUT_DATA_URL

    @property
    def expected_result_url(self):
        return EXPECTED_RESULT_URL

    @property
    def predictor_cls(self):
        return WarpPredictor

    def _check_result(self, result, expected_result):
        assert isinstance(result, DocTrResult)
        assert "input_img" in result
        result.pop("input_img")
        assert set(result) == set(expected_result)
        assert np.allclose(
            result["doctr_img"],
            np.array(expected_result["doctr_img"]),
            rtol=1e-2,
            atol=2,
        )