def load_annotations_gt(self):
ret = []
if self.rad_gt_format_coco_json.isChecked():
ret = converter.coco2bb(self.dir_annotations_gt)
elif self.rad_gt_format_cvat_xml.isChecked():
ret = converter.cvat2bb(self.dir_annotations_gt)
elif self.rad_gt_format_openimages_csv.isChecked():
ret = converter.openimage2bb(self.dir_annotations_gt,
self.dir_images_gt,
BBType.GROUND_TRUTH)
elif self.rad_gt_format_labelme_xml.isChecked():
ret = converter.labelme2bb(self.dir_annotations_gt)
elif self.rad_gt_format_pascalvoc_xml.isChecked():
ret = converter.vocpascal2bb(self.dir_annotations_gt)
elif self.rad_gt_format_imagenet_xml.isChecked():
ret = converter.imagenet2bb(self.dir_annotations_gt)
elif self.rad_gt_format_abs_values_text.isChecked():
ret = converter.text2bb(self.dir_annotations_gt,
bb_type=BBType.GROUND_TRUTH)
elif self.rad_gt_format_yolo_text.isChecked():
ret = converter.yolo2bb(self.dir_annotations_gt,
self.dir_images_gt,
self.filepath_classes_gt,
bb_type=BBType.GROUND_TRUTH)
# Make all types as GT
[bb.set_bb_type(BBType.GROUND_TRUTH) for bb in ret]
return ret
def test_converters_gts():
# Defining paths with images and annotations
images_dir = 'data/database/images'
gts_dir = 'data/database/gts'
assert os.path.isdir(images_dir)
assert os.path.isdir(gts_dir)
# COCO
coco_dir = os.path.join(gts_dir, 'coco_format_v1')
coco_bbs_v1 = converter.coco2bb(coco_dir)
coco_bbs_v1.sort(key=lambda x: str(x), reverse=True)
# COCO
coco_dir = os.path.join(gts_dir, 'coco_format_v2')
coco_bbs_v2 = converter.coco2bb(coco_dir)
coco_bbs_v2.sort(key=lambda x: str(x), reverse=True)
# CVAT
cvat_dir = os.path.join(gts_dir, 'cvat_format')
cvat_bbs = converter.cvat2bb(cvat_dir)
cvat_bbs.sort(key=lambda x: str(x), reverse=True)
# IMAGENET
imagenet_dir = os.path.join(gts_dir, 'imagenet_format/Annotations')
imagenet_bbs = converter.imagenet2bb(imagenet_dir)
imagenet_bbs.sort(key=lambda x: str(x), reverse=True)
# LABEL ME
labelme_dir = os.path.join(gts_dir, 'labelme_format')
labelme_bbs = converter.labelme2bb(labelme_dir)
labelme_bbs.sort(key=lambda x: str(x), reverse=True)
# OPEN IMAGE
openimage_dir = os.path.join(gts_dir, 'openimages_format')
openimage_bbs = converter.openimage2bb(openimage_dir, images_dir)
openimage_bbs.sort(key=lambda x: str(x), reverse=True)
# VOC PASCAL
vocpascal_dir = os.path.join(gts_dir, 'pascalvoc_format')
vocpascal_bbs = converter.vocpascal2bb(vocpascal_dir)
vocpascal_bbs.sort(key=lambda x: str(x), reverse=True)
# YOLO
yolo_annotations_dir = os.path.join(gts_dir, 'yolo_format/obj_train_data')
yolo_names_file = os.path.join(gts_dir, 'yolo_format/obj.names')
yolo_bbs = converter.yolo2bb(yolo_annotations_dir,
images_dir,
yolo_names_file,
bb_type=BBType.GROUND_TRUTH)
yolo_bbs.sort(key=lambda x: str(x), reverse=True)
assert len(coco_bbs_v1) == len(coco_bbs_v2) == len(cvat_bbs) == len(
imagenet_bbs) == len(labelme_bbs) == len(openimage_bbs) == len(
vocpascal_bbs) == len(yolo_bbs)
for coco_bb_v1, coco_bb_v2, cvat_bb, imagenet_bb, labelme_bb, openimage_bb, vocpascal_bb, yolo_bb in zip(
coco_bbs_v1, coco_bbs_v2, cvat_bbs, imagenet_bbs, labelme_bbs,
openimage_bbs, vocpascal_bbs, yolo_bbs):
assert coco_bb_v1 == coco_bb_v2 == cvat_bb == imagenet_bb == labelme_bb == openimage_bb == vocpascal_bb == yolo_bb