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a69d681 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 | import os
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_TO_NAME = {
"1": "car",
"2":"truck",
"3": "pickup",
"4": "tractor",
"5": "camping",
"6": "boat",
"7": "motorcycle",
"9": "bus",
"10": "van",
"11": "other",
"12": "small car",
"13": "large car",
"31": "plane",
"23": "board"
}
CATEGORY_ID_REMAPPING = {
"1": "0",
"2": "1",
"4": "2",
"5": "3",
"7": "4",
"9": "5",
"10": "6",
"11": "7",
"31": "8",
"23": "9"
}
NAME_TO_COCO_CATEGORY = {
"car": {"name": "car", "supercategory": "car"},
"truck": {"name": "truck", "supercategory": "truck"},
"tractor": {"name": "tractor", "supercategory": "tractor"},
"camping": {"name": "camping", "supercategory": "camping"},
"motorcycle": {"name": "motorcycle", "supercategory": "motorcycle"},
"bus": {"name": "bus", "supercategory": "bus"},
"van": {"name": "van", "supercategory": "van"},
"other": {"name": "other", "supercategory": "other"},
"plane": {"name": "plane", "supercategory": "plane"},
"board": {"name": "board", "supercategory": "board"}
}
def vedai_to_coco(
data_folder_dir,
split_images_path,
output_dir,
mode,
category_id_remapping=None,
):
"""
Converts vedai annotations into coco annotation.
Args:
data_folder_dir: str
'vedai' folder directory
split_images_path: str
split_images_path txt file
output_file_path: str
Output file path
mode: str
mode original|car_other|car
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) / "Vehicules512")
input_ann_folder = str(Path(data_folder_dir) / "Annotations512")
image_filepath_list = os.listdir(input_image_folder)
# Path(output_dir).parents[0].mkdir(parents=True, exist_ok=True)
if category_id_remapping is None:
category_id_remapping = CATEGORY_ID_REMAPPING
# init coco object
coco = Coco()
# append categories
if mode == 'original':
for category_id, category_name in CATEGORY_ID_TO_NAME.items():
if category_id in category_id_remapping.keys():
remapped_category_id = category_id_remapping[category_id]
coco_category = NAME_TO_COCO_CATEGORY[category_name]
coco.add_category(
CocoCategory(
id=int(remapped_category_id),
name=coco_category["name"],
supercategory=coco_category["supercategory"],
)
)
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 ['1','10']:
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 = {'1': '0','10': '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:
split_images_lst.append(line.strip().split('/')[1])
# convert vedai annotations to coco
for image_name in tqdm(image_filepath_list):
# get image properties
if image_name in split_images_lst:
image_filepath = str(Path(input_image_folder) / image_name)
annotation_filename = image_name.split("_co.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:
# parse annotation bboxes
new_line = line.strip("\n").split(" ")
y_corners = [int(x) for x in new_line[-4:]]
x_corners = [int(x) for x in new_line[-8:-4]]
minx_miny = (min(x_corners), min(y_corners))
maxx_maxy = (max(x_corners), max(y_corners))
#
i_bbox = [minx_miny[0], minx_miny[1], maxx_maxy[0], maxx_maxy[1]]
# width = maxx-minx, height = maxy-miny
width = i_bbox[2] - i_bbox[0]
height = i_bbox[3] - i_bbox[1]
#top left point
minx = min(x_corners)
miny = min(y_corners)
bbox = [minx,
miny,
width,
height]
# parse category id and name
category_id = new_line[3]
if category_id in category_id_remapping.keys():
category_name = CATEGORY_ID_TO_NAME[category_id]
remapped_category_id = category_id_remapping[category_id]
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 coco_annotation.area < 400:
coco_image.add_annotation(coco_annotation)
elif mode == 'car':
if coco_annotation.area < 400:
coco_image.add_annotation(coco_annotation)
coco.add_image(coco_image)
save_path = output_dir
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(vedai_to_coco) |