README.md

metadata

license: mit
task_categories:
  - image-classification
tags:
  - pcb
  - component-classification
  - electronics
  - computer-vision
  - random-forest
pretty_name: PCB Component Classifier Dataset
size_categories:
  - 1K<n<10K

PCB Component Classifier Dataset

1,120 individually photographed electronic components (resistors, capacitors, diodes, inductors, transistors, ICs), used to train an explainable Random-Forest classifier over 33 hand-engineered CV features.

Part of the PCB Inspection Suite. Pipeline, training code, and results: GitHub: pcb-component-classifier.

Classes and splits

Split	Images
train	1,000
holdout	120 (never used in training or tuning)

Class	Description
Resistors
Capacitors
Diodes
Inductors
Transistors
ICs

Format

Flat folders of <class>_<n>.png, one component per image, packaged as two archives:

• train.zip
• holdout.zip

Quick start

from huggingface_hub import hf_hub_download
import zipfile

for split in ["train", "holdout"]:
    zip_path = hf_hub_download(
        repo_id="ParsaVictor/pcb-component-classifier",
        repo_type="dataset",
        filename=f"{split}.zip",
    )
    with zipfile.ZipFile(zip_path) as zf:
        zf.extractall(split)

Related

• Trained model: pcb-component-classifier — 93.3% holdout accuracy, decision-path explanations
• Training code: GitHub: pcb-component-classifier
• Full suite overview: pcb-inspection-suite

License

MIT.