Python TrainImageGenerator.generate_sample示例

示例#1

    def test_finds_bounding_boxes(self):
        trainer = TrainImageGenerator(
            annotation_path="../../datasets/micro/annotations.csv",
            images_path="../../datasets/micro")
        x, y = trainer.generate_sample(0)

        found_boxes = interpret_label(y, FEATURE_MAPS)

        self.assertTrue(len(found_boxes) > 0)

示例#2

    def test_single_sample_generation(self):
        trainer = TrainImageGenerator(
            annotation_path="../../datasets/mini/annotations.csv",
            images_path="../../datasets/mini")
        x, y = trainer.generate_sample(0)

        self.assertEqual(np.shape(x), (300, 300, 3))
        self.assertEqual(len(y), len(FEATURE_MAPS))

        for layer, fm in zip(y, FEATURE_MAPS):
            self.assertEqual(fm.width, layer.shape[0])
            self.assertEqual(fm.height, layer.shape[1])
            self.assertEqual(len(fm.aspect_ratios), layer.shape[2])
            self.assertEqual(layer.shape[3], 5)

示例#3

文件： test_visualization.py 项目： mipo57/ssd_robosub

from postprocessing.visualization import visualize_prediction
from dataset_generation.data_feeder import TrainImageGenerator
from dataset_generation.augmenter import NoAgumenter

if __name__ == "__main__":
    generator = TrainImageGenerator("../../datasets/micro/annotations.csv",
                                    "../../datasets/micro",
                                    batch_size=1,
                                    augumenter=NoAgumenter())

    img, label = generator.generate_sample(0)
    visualize_prediction(img, label)