ParsaVictor/pcb-component-classifier
Image Classification • Updated • 1
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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.zipholdout.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.
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Models trained or fine-tuned on ParsaVictor/pcb-component-classifier