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x-not/
tool-detector

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Tool Detector

YOLOv8m detection model for handheld workshop tools, trained on synthetic rendered data and fine-tuned on real annotated images.

Intended to give a UR5 robot arm (5 kg payload, ~850 mm reach) tool identity and bounding-box location for pick-and-place tasks.

Model Details

Property	Value
Architecture	YOLOv8m
Input size	640 × 640
Classes	6 (current fine-tuned model)
Base weights	COCO pretrained `yolov8m.pt`
Fine-tuned on	Real annotated images (Label Studio export)

Classes

Index	Name
0	allen_key_set
1	allen_key
2	screw_driver
3	hammer
4	cutters
5	pliers

Usage

python

from ultralytics import YOLO
from huggingface_hub import hf_hub_download

weights = hf_hub_download(repo_id="x-not/tool-detector", filename="best.pt")
model = YOLO(weights)

results = model("your_image.jpg", conf=0.3)
results[0].show()

Or via the CLI:

bash

huggingface-cli download x-not/tool-detector best.pt --local-dir models/
yolo detect predict model=models/best.pt source=your_image.jpg conf=0.3

Training

Synthetic data generated with BlenderProc (Blender + Cycles): tools rendered as RGBA sprites at randomized pose/lighting, composited onto workshop background photos. Fine-tuned on real images annotated in Label Studio.

Source code and full training pipeline: github.com/NikolaasBender/Tool-Detector