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PCB Object Detection Dataset
A custom dataset for detecting 21 types of PCB (Printed Circuit Board) components using YOLO object detection.
Dataset Description
This dataset contains annotated images of PCB components for training YOLO-based object detection models. Each image contains multiple PCB components annotated with bounding boxes in YOLO format.
Classes (21)
| # | Class | Description |
|---|---|---|
| 0 | battery | Battery holders and cells |
| 1 | button | Push buttons |
| 2 | buzzer | Audio buzzers |
| 3 | capacitor | Capacitors (all types) |
| 4 | clock | Clock oscillators |
| 5 | connector | Connectors (USB, headers, etc.) |
| 6 | diode | Diodes and Zener diodes |
| 7 | display | LED displays and LCDs |
| 8 | fuse | Fuse holders and fuses |
| 9 | heatsink | Heat sinks |
| 10 | ic | Integrated circuits |
| 11 | inductor | Inductors and chokes |
| 12 | led | LEDs |
| 13 | pads | PCB pads |
| 14 | pins | PCB pins |
| 15 | potentiometer | Potentiometers and trimmers |
| 16 | relay | Relays |
| 17 | resistor | Resistors |
| 18 | switch | Toggle and slide switches |
| 19 | transformer | Transformers |
| 20 | transistor | Transistors |
Dataset Structure
PCB Object Detection Dataset/
├── train/
│ ├── images/ # Training images
│ └── labels/ # YOLO format annotations
├── valid/
│ ├── images/ # Validation images
│ └── labels/ # YOLO format annotations
├── test/
│ ├── images/ # Test images
│ └── labels/ # YOLO format annotations
├── data.yaml # Dataset configuration
└── README.md # This file
Dataset Statistics
| Split | Images |
|---|---|
| Train | 1,788 |
| Validation | 173 |
| Test | Available |
Annotation Format
YOLO format: class_id x_center y_center width height
Example:
0 0.5 0.5 0.1 0.2
10 0.3 0.4 0.05 0.08
How to Use with Ultralytics
from ultralytics import YOLO
# Train a model
model = YOLO("yolov8s.pt")
model.train(data="path/to/data.yaml", epochs=100, imgsz=640)
# Run inference
results = model.predict("path/to/image.jpg", conf=0.25)
How to Use with this Dataset
Option 1: Download from Roboflow
- Go to Roboflow Universe
- Click "Download" and select "YOLO v8" format
- Extract to this directory
Option 2: Use the prepare script
python pcb_yolo/scripts/prepare_dataset.py --config pcb_yolo/configs/data_config.yaml --download
data.yaml
path: ./PCB Object Detection Dataset
train: train/images
val: valid/images
test: test/images
nc: 21
names:
- battery
- button
- buzzer
- capacitor
- clock
- connector
- diode
- display
- fuse
- heatsink
- ic
- inductor
- led
- pads
- pins
- potentiometer
- relay
- resistor
- switch
- transformer
- transistor
Citation
If you use this dataset, please cite:
@misc{pcb_object_detection_dataset,
title={PCB Object Detection Dataset},
author={Arshia},
year={2026},
publisher={Hugging Face},
note={21-class PCB component detection dataset for YOLO}
}
License
This dataset is released under the MIT License.
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