Datasets of cracks for deep learning. A standarized way to create a public dataset of fish (images -> labelling -> dataset exports). If you want to add more images create an issue.
- Crackv1: CRACK9001 (INSER MODEL HERE) - Not ready
- All datasets available on: (INSER GD LINK) Link to Google Drive ✔️
Thanks to Roboflow, we can export for different formats:
- Powered by CVAT (All images original size): JSON (
COCO
,Datumaro
), XML (CVAT Image
,CVAT Video
,LabelMe
,PASCAL VOC
), TXT (MOT
,YOLO
), JPG,PNG (ImageNet
,Segmentation Mask
), Others (Tensorflow TFRecord
).
Choose just one zip file for one model, select the zip file accord to your model or download all the exports on release section
Date | Images | Classes | Download dataset & Code (TR70/VL20/TS10) |
---|---|---|---|
2021-01-19 | - (Orig) | - | CRACK9001 ✔️ |
Example code to use only with Roboflow notebooks to use the repo and locate correctly.
# Instead of doing:
!curl -L "ROBOFLOW LINK" > roboflow.zip; unzip roboflow.zip; rm roboflow.zip
# Use:
!gdown --id "ID OF THE GOOGLE DRIVE ZIP" > roboflow.zip; unzip roboflow.zip; rm roboflow.zip
Keywords to find these datasets: fish, trout
Date | Powered by | Author |
---|---|---|
2021-01-20 | Kaggle | CRACK0006 - Concrete_crack_detection |
2021-01-20 | Kaggle | CRACK0005 - Crack Segmentation Dataset |
2021-01-19 | Mendeley | CRACK0004 - Concrete Crack Images for Classification |
2021-01-19 | Kaggle | CRACK0003 - Concrete Crack Images for Classification |
2021-01-19 | Kaggle | CRACK0002 - Structural Defects Network (SDNET) 2018 |
2021-01-19 | Kaggle | CRACK0001 - Surface Crack Detection |
There's a guide to help creating this dataset standardized and exported to a multiple standards. Click here
This repository is under MIT LICENSE.