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from pathlib import Path | |
import cv2 | |
import numpy as np | |
from isegm.data.base import ISDataset | |
from isegm.data.sample import DSample | |
class DavisDataset(ISDataset): | |
def __init__( | |
self, dataset_path, images_dir_name="img", masks_dir_name="gt", **kwargs | |
): | |
super(DavisDataset, self).__init__(**kwargs) | |
self.dataset_path = Path(dataset_path) | |
self._images_path = self.dataset_path / images_dir_name | |
self._insts_path = self.dataset_path / masks_dir_name | |
self.dataset_samples = [x.name for x in sorted(self._images_path.glob("*.*"))] | |
self._masks_paths = {x.stem: x for x in self._insts_path.glob("*.*")} | |
def get_sample(self, index) -> DSample: | |
image_name = self.dataset_samples[index] | |
image_path = str(self._images_path / image_name) | |
mask_path = str(self._masks_paths[image_name.split(".")[0]]) | |
image = cv2.imread(image_path) | |
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
instances_mask = np.max(cv2.imread(mask_path).astype(np.int32), axis=2) | |
instances_mask[instances_mask > 0] = 1 | |
return DSample(image, instances_mask, objects_ids=[1], sample_id=index) | |