Skip to content

yolo2coco.py: polygon label support #1031

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from
Open

yolo2coco.py: polygon label support #1031

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
45 changes: 25 additions & 20 deletions tools/dataset_converters/yolo2coco.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -45,12 +45,14 @@
`tools/analysis_tools/browse_coco_json.py` script to visualize
whether it is correct.
"""

import argparse
import os
import os.path as osp

import mmcv
import mmengine
import numpy as np

IMG_EXTENSIONS = ('.jpg', '.png', '.jpeg')

Expand All @@ -72,36 +74,39 @@ def get_image_info(yolo_image_dir, idx, file_name):
'file_name': file_name,
'id': idx,
'width': width,
'height': height
'height': height,
}
return img_info_dict, height, width


def convert_bbox_info(label, idx, obj_count, image_height, image_width):
"""Convert yolo-style bbox info to the coco format."""
def convert_label_info(label, idx, obj_count, image_height, image_width):
"""Convert yolo-style label info to the coco format."""
label = label.strip().split()
x = float(label[1])
y = float(label[2])
w = float(label[3])
h = float(label[4])

# convert x,y,w,h to x1,y1,x2,y2
x1 = (x - w / 2) * image_width
y1 = (y - h / 2) * image_height
x2 = (x + w / 2) * image_width
y2 = (y + h / 2) * image_height

if len(label) < 7: # box case
xc, yc, w, h = map(float, label[1:5])
xmin = (xc - w / 2) * image_width
ymin = (yc - h / 2) * image_height
xmax = (xc + w / 2) * image_width
ymax = (yc + h / 2) * image_height
vertices = [xmin, ymin, xmax, ymin, xmax, ymax, xmin, ymax]
else: # polygon case
vertices = np.array(label[1:]).astype(float)
vertices = vertices.reshape(-1, 2) * [image_width, image_height]
xmin, ymin = vertices.min(axis=0)
xmax, ymax = vertices.max(axis=0)
vertices = list(vertices.flatten())

cls_id = int(label[0])
width = max(0., x2 - x1)
height = max(0., y2 - y1)
width = max(0.0, xmax - xmin)
height = max(0.0, ymax - ymin)
coco_format_info = {
'image_id': idx,
'id': obj_count,
'category_id': cls_id,
'bbox': [x1, y1, width, height],
'bbox': [xmin, ymin, width, height],
'area': width * height,
'segmentation': [[x1, y1, x2, y1, x2, y2, x1, y2]],
'iscrowd': 0
'segmentation': [vertices],
'iscrowd': 0,
}
obj_count += 1
return coco_format_info, obj_count
Expand Down Expand Up @@ -226,7 +231,7 @@ def convert_yolo_to_coco(image_dir: str):
with open(label_path) as f:
labels = f.readlines()
for label in labels:
coco_info, obj_count = convert_bbox_info(
coco_info, obj_count = convert_label_info(
label, idx, obj_count, image_height, image_width)
dataset['annotations'].append(coco_info)
converted += 1
Expand Down