Top Concrete Datasets and Models
The datasets below can be used to train fine-tuned models for concrete detection. You can explore each dataset in your browser using Roboflow and export the dataset into one of many formats.
At the bottom of this page, we have guides on how to train a model using the concrete datasets below.
by Yifeng Chen
2742 images 13 classes
88 images 25 classes
by Labeling
50 images 14 classes
500 images 7 classes
by hychoi
3468 images 14 classes
by testing
997 images 13 classes
by RMIT
78 images 14 classes
200 images 5 classes
by osmando
706 images 1342 classes
animal car drink mushroom rock wine glass 2 bottles on a rock next to fruit in front of orange background. 2 brown paper boxes in front of light brown background 2 cream bottles in front of blue tiles 2 macarons on a rock block in front of light orange background 3 black bottles next to yellow stairs and dry flower with shadow 3 blue bottles on blue plates next to dry nuts 3 bottles in front of light background with shadows 3 bottles in front of light brown background with shadows. 3 bottles in front of light gray background with shadows of a plant. 3 boxes in front of dark background 3 perfume bottles on reflective gray surface 4 paper boxes in front of light yellow background 4 potteries on a marble table 6 white bowls of spices on a wooden surface
30 images 10 classes
by images
163 images 18 classes
2412 images 28 classes
Arching (concrete) Barrier damage Block cracks (asphalt) Broken board (cement) Corner fracture (cement) Crack (cement) Cracking (asphalt) Curb defect Defective protective facilities Edge spalling (cement) Exposed (cement) Joint material damage (cement) Longitudinal cracks (asphalt) Loose (asphalt) Marker defects Mud pumping (cement) Oiled (asphalt) Patching (asphalt) Potholes (asphalt) Potholes (concrete)