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yolo2coco.py: polygon label support #1031

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yolo2coco.py: polygon label support #1031

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45 changes: 25 additions & 20 deletions tools/dataset_converters/yolo2coco.py
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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