File size: 6,941 Bytes
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from pathlib import Path
import fire
from PIL import Image
from sahi.utils.coco import Coco, CocoAnnotation, CocoCategory, CocoImage
from sahi.utils.file import save_json
from tqdm import tqdm
import sys
CATEGORY_ID_REMAPPING = {
"plane": "0",
"baseball-diamond": "1",
"bridge": "2",
"ground-track-field": "3",
"small-vehicle": "4",
"large-vehicle": "5",
"ship": "6",
"tennis-court": "7",
"basketball-court": "8",
"storage-tank": "9",
"soccer-ball-field": "10",
"roundabout": "11",
"harbor": "12",
"swimming-pool": "13",
"helicopter": "14",
"container-crane": "15",
"airport": "16",
"helipad": "17"
}
def dota2_to_coco(
data_folder_dir,
split_images_path,
output_file_path,
mode,
category_id_remapping=None,
):
"""
Converts dota2 annotations into coco annotation.
Args:
data_folder_dir: str
'fair1m' folder directory
output_file_path: str
Output file path
category_id_remapping: dict
Used for selecting desired category ids and mapping them.
If not provided, vedai mapping will be used.
format: str(id) to str(id)
"""
# init paths/folders
input_image_folder = str(Path(data_folder_dir) / "images")
input_ann_folder = str(Path(data_folder_dir) / "labelTxt")
image_filepath_list = os.listdir(input_image_folder)
if category_id_remapping is None:
category_id_remapping = CATEGORY_ID_REMAPPING
# init coco object
coco = Coco()
if mode == 'original':
# append categories
categories = ["plane", "baseball-diamond", "bridge", "ground-track-field", "small-vehicle", "large-vehicle", "ship", "tennis-court", "basketball-court", "storage-tank", "soccer-ball-field", "roundabout", "harbor", "swimming-pool", "helicopter", "container-crane", "airport", "helipad"]
for i, cat in enumerate(categories):
coco.add_category(CocoCategory(id=i, name=cat))
elif mode == 'car_other':
print('"car_other" mode categories')
coco.add_category(CocoCategory(id=0, name='Other'))
coco.add_category(CocoCategory(id=1, name='Car'))
for k,v in category_id_remapping.items():
if k in 'small-vehicle':
category_id_remapping[k] =1
else:
category_id_remapping[k]=0
elif mode == 'car':
# car related categories: car, pickup, van
print('"car" mode categories')
coco.add_category(CocoCategory(id=0, name='Car'))
category_id_remapping = {'small-vehicle': '0'}
else:
print('pick a defined mode: [original/car_other/car]')
sys.exit()
split_images_lst = []
with open(split_images_path, 'r') as f:
for line in f:
broken = line.strip().split('/')
if len(broken) > 1:
split_images_lst.append(broken[1])
else:
split_images_lst.append(broken[0])
cnt=0
broken_set = set()
# convert fair1m annotations to coco
for image_filename in tqdm(image_filepath_list):
if image_filename in split_images_lst:
cnt+=1
# get image properties
image_filepath = str(Path(input_image_folder) / image_filename)
annotation_filename = image_filename.split(".png")[0] + ".txt"
annotation_filepath = str(Path(input_ann_folder) / annotation_filename)
image = Image.open(image_filepath)
cocoimage_filename = str(Path(image_filepath)).split(str(Path(data_folder_dir)))[1]
if cocoimage_filename[0] == os.sep:
cocoimage_filename = cocoimage_filename[1:]
# create coco image object
coco_image = CocoImage(file_name=cocoimage_filename, height=image.size[1], width=image.size[0])
# parse annotation file
###
file = open(annotation_filepath, "r")
lines = file.readlines()
for line in lines:
# x1 y1 x2 y2 x3 y3 x4 y4 category difficult
broken = line.strip().split(' ')
broken_set.add(len(broken))
if len(broken) > 1:
x_corners = []
y_corners = []
x_corners.append(int(float(broken[0])))
x_corners.append(int(float(broken[2])))
x_corners.append(int(float(broken[4])))
x_corners.append(int(float(broken[6])))
#
y_corners.append(int(float(broken[1])))
y_corners.append(int(float(broken[3])))
y_corners.append(int(float(broken[5])))
y_corners.append(int(float(broken[7])))
minx = min(x_corners)
miny = min(y_corners)
maxx = max(x_corners)
maxy = max(y_corners)
tbox = [minx, miny, maxx, maxy]
# width = maxx-minx, height = maxy-miny
width = tbox[2] - tbox[0]
height = tbox[3] - tbox[1]
bbox = [minx,
miny,
width,
height]
obj_area = width * height
category_name = broken[8]
if category_name in category_id_remapping.keys():
remapped_category_id = category_id_remapping[category_name]
else:
continue
# create coco annotation and append it to coco image
coco_annotation = CocoAnnotation.from_coco_bbox(
bbox=bbox,
category_id=int(remapped_category_id),
category_name=category_name,
)
if mode == 'original':
if coco_annotation.area > 0:
coco_image.add_annotation(coco_annotation)
elif mode == 'car_other':
if 0 < coco_annotation.area < 400:
coco_image.add_annotation(coco_annotation)
elif mode == 'car':
if 0 < coco_annotation.area < 400:
# if 0 < obj_area < 400:
coco_image.add_annotation(coco_annotation)
else:
continue
coco.add_image(coco_image)
print('cnt', cnt, 'broken_set', broken_set)
save_path = output_file_path
all_json_path = Path(save_path) / "{}.json".format(split_images_path.split('.')[0])
save_json(data=coco.json, save_path=all_json_path)
if __name__ == "__main__":
fire.Fire(dota2_to_coco)
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