Datasets:
File size: 3,130 Bytes
9f22904 | 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 | import json
import os
import cv2
import numpy as np
from datetime import datetime
def yolo_to_coco(image_dir, label_dir, output_json, split="Train", author="Noone", version="1.0"):
coco = {
"info": {
"description": "TinyBubble Dataset",
"url": "",
"version": version,
"split": split,
"year": datetime.now().year,
},
"images": [],
"annotations": [],
"categories": [{"id": 0, "name": "bubble", "supercategory": "none"}]
}
ann_id = 0
image_id = 0
for img_file in os.listdir(image_dir):
if not img_file.endswith(('.png', '.jpg', '.jpeg','.tiff','.tif')):
continue
img_path = os.path.join(image_dir, img_file)
img = cv2.imread(img_path)
if img is None: continue
height, width, _ = img.shape
coco["images"].append({
"id": image_id,
"file_name": img_file,
"width": width,
"height": height
})
label_file = os.path.splitext(img_file)[0] + ".txt"
label_path = os.path.join(label_dir, label_file)
if os.path.exists(label_path):
with open(label_path, 'r') as f:
lines = list(dict.fromkeys([line.strip() for line in f.readlines() if line.strip()]))
for line in lines:
parts = list(map(float, line.split()))
class_id = int(parts[0])
coords = parts[1:]
abs_coords = []
for i in range(0, len(coords), 2):
abs_coords.append(coords[i] * width)
abs_coords.append(coords[i+1] * height)
xs = abs_coords[0::2]
ys = abs_coords[1::2]
x1, y1, x2, y2 = min(xs), min(ys), max(xs), max(ys)
bbox = [x1, y1, x2 - x1, y2 - y1]
area = cv2.contourArea(np.array(abs_coords).reshape(-1, 2).astype(np.float32))
coco["annotations"].append({
"id": ann_id,
"image_id": image_id,
"category_id": class_id,
"segmentation": [abs_coords],
"area": area,
"bbox": bbox,
"iscrowd": 0
})
ann_id += 1
image_id += 1
with open(output_json, 'w') as f:
json.dump(coco, f, indent=4)
print(f"COCO annotation saved as: {output_json}")
yolo_to_coco(
image_dir="../../../tinybubble/yolo_seg/train/images",
label_dir="../../../tinybubble/yolo_seg/train/labels",
output_json="../../../tinybubble/coco/annotations/1.0_train_coco.json",
split="Train",
version="1.0"
)
yolo_to_coco(
image_dir="../../../tinybubble/yolo_seg/val/images",
label_dir="../../../tinybubble/yolo_seg/val/labels",
output_json="../../../tinybubble/coco/annotations/1.0_val_coco.json",
split="Val",
version="1.0"
) |