Object Detection
welding-defect-object-detection
Welding Defect Object Detection
2,028 annotated images of welds for defect detection, in both YOLO and COCO
formats. Three classes:
id (YOLO / COCO)
name
0 / 1
Bad Weld
1 / 2
Good Weld
2 / 3
Defect
Splits
split
images
annotations
train
1,619
4,583
valid
283
802
test
126
301
Layout
├── data.yaml # YOLO class names + split paths
├── train|valid|test/
│ ├── images/ # .jpg
│ └── labels/… See the full description on the dataset page: https://huggingface.co/datasets/rikkarth/welding-defect-object-detection.license-plate-object-detection
Dataset Labels
['license_plate']
Number of Images
{'train': 6176, 'valid': 1765, 'test': 882}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds = load_dataset("keremberke/license-plate-object-detection", name="full")
example = ds['train'][0]
Roboflow Dataset Page
https://universe.roboflow.com/augmented-startups/vehicle-registration-plates-trudk/dataset/1
Citation… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/license-plate-object-detection.X4_SWIR_Industrial_Foreign_Object_Detection_Bedding
Hyperspectral Foreign-Object Detection in Bedding — Full Dataset (VIS + SWIR)
A 6-band VIS+SWIR hyperspectral dataset for industrial foreign-object
detection on a bedding substrate (a tray of wood-shaving / sawdust animal
bedding). Captured with a Cubert Ultris X4 + SWIR rig — 6 spectral bands
at 450 / 550 / 625 nm (VIS) and 1050 / 1200 / 1450 nm (SWIR), 2400 × 4900
pixels per frame. 252 frames (193 train · 59 val), 51 frames carry
pixel-level polygon… See the full description on the dataset page: https://huggingface.co/datasets/cubert-gmbh/X4_SWIR_Industrial_Foreign_Object_Detection_Bedding.construction-safety-object-detection
Dataset Labels
['barricade', 'dumpster', 'excavators', 'gloves', 'hardhat', 'mask', 'no-hardhat', 'no-mask', 'no-safety vest', 'person', 'safety net', 'safety shoes', 'safety vest', 'dump truck', 'mini-van', 'truck', 'wheel loader']
Number of Images
{'train': 307, 'valid': 57, 'test': 34}
How to Use
Install datasets:
pip install datasets
Load the dataset:
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/keremberke/construction-safety-object-detection.Pizza-Toppings-Object-DetectionXMR_Industrial_Foreign_Object_Detection_Lentils
Hyperspectral Foreign-Object Detection in Lentils — Full Dataset
The larger counterpart to the small tutorial demo at
cubert-gmbh/XMR_Demo_Industrial_Foreign_Object_Detection_Lentils.
Captured with a Cubert Ultris XMR camera — 61 bands per pixel, 430–910 nm, 1080 × 1000 pixels. Three acquisition days, 15 merged .cu3s capture sessions, 1,136 frames total, 696 frames with pixel-level COCO annotations across 7 foreign-object classes.
Foreign-object detection in… See the full description on the dataset page: https://huggingface.co/datasets/cubert-gmbh/XMR_Industrial_Foreign_Object_Detection_Lentils.