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Blueprint OCR Dataset (YOLO Format)

Images resized to 50% resolution for faster training and smaller download size.

Quick Start

from huggingface_hub import hf_hub_download
import zipfile

# Download
zip_path = hf_hub_download(
    repo_id="packshotter/blueprint-dataset",
    filename="blueprint-dataset.zip",
    repo_type="dataset"
)

# Extract
with zipfile.ZipFile(zip_path, 'r') as z:
    z.extractall('.')

# Train with YOLOv8
from ultralytics import YOLO
model = YOLO('yolov8n.pt')
model.train(data='ocr_yolo_half/data.yaml', epochs=100, imgsz=640)

Statistics

Split Images
Train 9,018
Val 1,129

23 Classes

ID Name
0 공간_다목적공간
1 공간_엘리베이터홀
2 공간_계단실
3 객체_변기
4 객체_세면대
5 객체_싱크대
6 객체_욕조
7 객체_가스레인지
8 구조_출입문
9 구조_창호
10 구조_벽체
11 background
12 공간_거실
13 공간_침실
14 공간_주방
15 공간_현관
16 공간_발코니
17 공간_화장실
18 공간_실외기실
19 공간_드레스룸
20 OCR
21 공간_기타
22 공간_엘리베이터

Structure (after extraction)

ocr_yolo_half/
├── data.yaml          # YOLO config
├── images/
│   ├── train/         # 9,018 images (1754x2481)
│   └── val/           # 1,129 images
└── labels/
    ├── train/         # YOLO format .txt
    └── val/
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