VIA数据集格式转COCO格式（以气球数据集为例）
1.数据准备
将气球数据集下载到本地，解压后的数据集，数据集截图如下
2.转换格式
新建一个coco_format.py的文件，将下述代码复制进去，注意需要将第3行路径改为自己的绝对路径
import convert as via2coco
data_path = '/home/xxx/mmdetection/data/'
for keyword in ['train', 'val']:
input_dir = data_path + 'balloon/' + keyword + '/'
input_json = input_dir + 'via_region_data.json'
categories = ['balloon']
super_categories = ['N/A']
output_json = input_dir + 'custom_' + keyword + '.json'
print('Converting {} from VIA format to COCO format'.format(input_json))
coco_dict = via2coco.convert(
imgdir=input_dir,
annpath=input_json,
categories=categories,
super_categories=super_categories,
output_file_name=output_json,
first_class_index=first_class_index,
)
新建一个convert.py的文件，将下述代码复制进去
import os
from PIL import Image
import datetime
import json
import getArea
def create_image_info(
image_id,
file_name,
image_size,
date_captured=datetime.datetime.utcnow().isoformat(" "),
license_id=1,
coco_url="",
flickr_url="",
):
image_info = {
"id": image_id,
"file_name": file_name,
"width": image_size[0],
"height": image_size[1],
"date_captured": date_captured,
"license": license_id,
"coco_url": coco_url,
"flickr_url": flickr_url,
}
return image_info
def create_annotation_info(
annotation_id, image_id, category_id, is_crowd, area, bounding_box, segmentation
):
annotation_info = {
"id": annotation_id,
"image_id": image_id,
"category_id": category_id,
"iscrowd": is_crowd,
"area": area, # float
"bbox": bounding_box, # [x,y,width,height]
"segmentation": segmentation, # [polygon]
}
return annotation_info
def get_segmenation(coord_x, coord_y):
seg = []
for x, y in zip(coord_x, coord_y):
seg.append(x)
seg.append(y)
return [seg]
def convert(
imgdir,
annpath,
categories=None,
super_categories=None,
output_file_name=None,
first_class_index=1, # typically, 0 or 1
):
"""
:param imgdir: directory for your images
:param annpath: path for your annotations
:return: coco_output is a dictionary of coco style which you could dump it into a json file
as for keywords 'info','licenses','categories',you should modify them manually
"""
if categories is None:
categories = ["rib", "clavicle"]
default_category = categories[0]
category_dict = dict()
for (cat_id, cat_name) in enumerate(categories, start=first_class_index):
category_dict[cat_name] = cat_id
if super_categories is None:
default_super_category = "bone"
super_categories = [default_super_category for _ in categories]
coco_output = {
}
coco_output["info"] = {
"description": "Example Dataset",
"url": "https://github.com/waspinator/pycococreator",
"version": "0.1.0",
"year": 2018,
"contributor": "waspinator",
"date_created": datetime.datetime.utcnow().isoformat(" "),
}
coco_output["licenses"] = [
{
"id": 1,
"name": "Attribution-NonCommercial-ShareAlike License",
"url": "http://creativecommons.org/licenses/by-nc-sa/2.0/",
}
]
coco_output["categories"] = [
{
"id": category_dict[cat_name],
"name": cat_name,
"supercategory": super_cat_name,
}
for (cat_name, super_cat_name) in zip(categories, super_categories)
]
coco_output["images"] = []
coco_output["annotations"] = []
ann = json.load(open(annpath))
# annotations id start from zero
ann_id = 0
# in VIA annotations, keys are image name
for img_id, key in enumerate(ann.keys()):
filename = ann[key]["filename"]
img = Image.open(imgdir + filename)
# make image info and storage it in coco_output['images']
image_info = create_image_info(
img_id, os.path.basename(filename), image_size=img.size
)
# Caveat: image shapes are conventionally (height, width) whereas image sizes are conventionally (width, height)
# References:
# - https://note.nkmk.me/en/python-opencv-pillow-image-size/
# - https://github.com/facebookresearch/detectron2/blob/master/detectron2/data/detection_utils.py#L189
coco_output["images"].append(image_info)
regions = ann[key]["regions"]
# for one image ,there are many regions,they share the same img id
for region in regions:
region_attributes = regions[region]["region_attributes"]
try:
cat_name = region_attributes["label"]
except KeyError:
cat_name = default_category
try:
cat_id = category_dict[cat_name]
except KeyError:
print("Skipping unknown category {} in {}".format(cat_name, filename))
continue
iscrowd = 0
shape_attributes = regions[region]["shape_attributes"]
points_x = shape_attributes["all_points_x"]
points_y = shape_attributes["all_points_y"]
area = getArea.GetAreaOfPolyGon(points_x, points_y)
min_x = min(points_x)
max_x = max(points_x)
min_y = min(points_y)
max_y = max(points_y)
box = [min_x, min_y, max_x - min_x, max_y - min_y]
segmentation = get_segmenation(points_x, points_y)
# make annotations info and storage it in coco_output['annotations']
ann_info = create_annotation_info(
ann_id, img_id, cat_id, iscrowd, area, box, segmentation
)
coco_output["annotations"].append(ann_info)
ann_id = ann_id + 1
if output_file_name is not None:
print("Saving to {}".format(output_file_name))
with open(output_file_name, "w") as f:
json.dump(coco_output, f)
return coco_output
if __name__ == "__main__":
input_dir = "/content/data/balloon/train/"
input_json = input_dir + "via_region_data.json"
categories = ["balloon"]
super_categories = ["N/A"]
output_json = input_dir + "coco_train.json"
coco_dict = convert(
imgdir=input_dir,
annpath=input_json,
categories=categories,
super_categories=super_categories,
output_file_name=output_json,
)
新建一个getArea.py的文件，将下述代码复制进去
# -*- coding: cp936 -*-
import math
class Point:
def __init__(self, x, y):
self.x = x
self.y = y
def GetAreaOfPolyGon(points_x, points_y):
points = []
for index in range(len(points_x)):
points.append(Point(points_x[index], points_y[index]))
area = 0
if len(points) < 3:
raise Exception("error")
p1 = points[0]
for i in range(1, len(points) - 1):
p2 = points[1]
p3 = points[2]
vecp1p2 = Point(p2.x - p1.x, p2.y - p1.y)
vecp2p3 = Point(p3.x - p2.x, p3.y - p2.y)
vecMult = vecp1p2.x * vecp2p3.y - vecp1p2.y * vecp2p3.x
sign = 0
if vecMult > 0:
sign = 1
elif vecMult < 0:
sign = -1
triArea = GetAreaOfTriangle(p1, p2, p3) * sign
area += triArea
return abs(area)
def GetAreaOfTriangle(p1, p2, p3):
area = 0
p1p2 = GetLineLength(p1, p2)
p2p3 = GetLineLength(p2, p3)
p3p1 = GetLineLength(p3, p1)
s = (p1p2 + p2p3 + p3p1) / 2
area = s * (s - p1p2) * (s - p2p3) * (s - p3p1)
area = math.sqrt(area)
return area
def GetLineLength(p1, p2):
length = math.pow((p1.x - p2.x), 2) + math.pow((p1.y - p2.y), 2)
length = math.sqrt(length)
return length
def main():
points = []
# x=[0.02,0.04,0.05,0.07,0.10,0.12,0.15,0.18,0.21,0.24,0.28,0.32,0.37,0.42,0.46,0.52,0.57,0.62,0.68,0.74,0.80,0.86,0.92,0.99,1.06,1.12,1.19,1.26,1.33,1.40,1.48,1.68,1.75,1.82,1.88,1.95,2.01,2.08,2.15,2.21,2.28,2.35,2.41,2.48,2.55,2.61,2.68,2.75,2.81,2.88,2.95,3.01,3.08,3.15,3.21,3.27,3.34,3.39,3.46,3.51,3.58,3.64,3.69,3.75,3.81,3.86,3.92,3.97,4.02,4.08,4.13,4.17,4.22,4.27,4.31,4.36,4.41,4.44,4.49,4.52,4.56,4.60,4.64,4.67,4.71,4.74,4.77,4.80,4.82,4.85,4.87,4.89,4.91,4.93,4.94,4.96,4.97,4.98,4.99,4.99,4.99,4.99,4.99,4.99,4.98,4.97,4.96,4.94,4.93,4.91,4.88,4.86,4.83,4.80,4.77,4.73,4.70,4.66,4.62,4.57,4.52,4.46,4.42,4.36,4.29,4.24,4.18,4.11,4.06,3.99,3.92,3.85,3.78,3.70,3.63,3.55,3.48,3.41,3.33,3.26,3.18,3.09,3.02,2.94,2.85,2.78,2.69,2.61,2.54,2.45,2.37,2.30,2.21,2.13,2.06,1.98,1.89,1.82,1.74,1.67,1.59,1.52,1.45,1.37,1.30,1.23,1.16,1.09,1.03,0.96,0.90,0.84,0.78,0.72,0.67,0.61,0.55,0.51,0.45,0.41,0.36,0.32,0.28,0.24,0.21,0.18,0.14,0.12,0.09,0.07,0.05,0.04,0.02,0.01,0.01,0.00]
x = [1, 0, 0, 1]
y = [0, 0, 1, 1]
# y=[37.23,38.91,40.61,41.66,43.01,45.78,49.20,51.85,53.81,56.15,58.65,57.61,55.97,54.22,52.13,50.91,51.01,51.65,52.28,53.65,54.56,54.53,54.43,53.75,52.45,51.85,51.76,51.75,51.80,52.42,52.42,52.47,52.60,52.75,52.83,52.55,52.35,52.25,52.01,51.82,51.82,51.81,51.85,51.88,51.88,51.81,51.80,51.75,51.53,51.49,51.54,51.51,51.51,51.52,51.51,51.48,51.52,51.26,51.09,51.05,50.92,50.93,50.97,50.97,50.95,51.02,50.99,51.04,51.04,50.92,50.65,50.64,50.61,50.61,50.66,50.67,50.64,50.67,50.58,50.47,50.45,50.24,50.07,50.10,50.07,50.05,50.11,50.10,50.07,49.97,49.70,49.67,49.68,49.50,49.50,49.49,49.47,49.50,49.46,49.48,49.21,48.11,47.81,47.37,47.32,46.85,45.77,44.54,43.09,41.66,40.29,38.49,36.54,33.99,31.23,28.23,25.26,23.25,24.20,26.10,29.01,31.74,33.24,33.20,32.61,30.41,27.65,26.16,25.95,25.98,27.61,29.39,31.12,31.89,31.97,30.75,29.65,28.33,27.31,27.00,27.47,28.33,29.30,30.26,30.96,30.99,30.31,29.17,28.83,28.18,28.16,28.18,28.94,29.49,30.08,30.34,30.43,30.24,29.58,29.15,29.08,29.08,29.41,29.76,30.36,30.48,30.55,30.48,30.47,30.14,29.80,29.80,30.17,30.39,30.85,31.42,31.55,31.53,31.54,31.48,31.43,31.40,31.41,31.57,32.01,32.66,33.24,33.25,33.24,33.24,32.80,32.25,32.25,32.40,32.61,33.04]
for index in range(len(x)):
points.append(Point(x[index], y[index]))
area = GetAreaOfPolyGon(points)
print(area)
# print(math.ceil(area))
# assert math.ceil(area)==1
if __name__ == "__main__":
main()
最后，使用python coco_format.py运行程序即可