Related Objects of Interest: * export, train, and deploy computer vision models, visit https://github.com/roboflow/notebooks, * collaborate with your team on computer vision projects, * collect & organize images, * understand and search unstructured image data, * use active learning to improve your dataset over time, ==============================, for state of the art computer vision training notebooks you can use with this dataset,, the following pre-processing was applied to each image:, * annotate, and create datasets
Top The Datasets and Models
The datasets below can be used to train fine-tuned models for the 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 the datasets below.
by ANPR
4000 images 32 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25 26 27 28 29 30
by Raj Das
6040 images 36 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 18 19 20 21 22 23 24 25 26 27 28 29 30
1760 images 38 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random shear of between -15° to +15° horizontally and -15° to +15° vertically * Resize to 416x416 (Stretch) * Salt and pepper noise was applied to 4 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 21 22 23 24 25 26 27 28 29 30
600 images 48 classes
elephant fox monkey pig tiger * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25
by CPDOCR
2555 images 21 classes
by Car damage
9129 images 31 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Random brigthness adjustment of between -25 and +25 percent * Random rotation of between -15 and +15 degrees * Resize to 640x640 (Stretch) * Salt and pepper noise was applied to 5 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 26 27 28 29 30 ============================== Car-damage are annotated in YOLOv8 format.
by My Workspace
52 images 30 classes
by grad project
523 images 40 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data 1 19 2 20 21 23 3 4 5 6 7 8 9 ==============================
by kaushik
8015 images 78 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Random Gaussian blur of between 0 and 3.25 pixels * Randomly crop between 0 and 33 percent of the image * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 100 120 21 22 23 24 25 26 27 28
60 images 50 classes
Bad road surface Cattle on the road. Children Children Walking Crossing for pedestrians Crossroad side roads on the left and right Crossroad with a side road on the left Crossroad with side road on the right. Curve to the right Danger with no specific traffic sign. Deer on the road or unsafe for animal Dip in the road Double Curve Falling rocks Give away Give way Limited height Loose chippings on the road surface Low-flying aircrafts. Narrowing on the left
by bcvt
9760 images 33 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 1.5 pixels * Random rotation of between -15 and +15 degrees * Salt and pepper noise was applied to 5 percent of pixels * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 21 22 23 24 25 26 27 28 29 30
by SnowWhite
200 images 85 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 160x160 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 01 03 04 05 07 09 19 20 21 22 23 24
by companyname
129 images 83 classes
Large parts Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof Large parts-Trunk lid Large parts-Windshield
by companyname
129 images 83 classes
Large parts Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof Large parts-Trunk lid Large parts-Windshield
by companyname
742 images 86 classes
Large parts Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof Large parts-Trunk lid Large parts-Windshield
by companyname
695 images 84 classes
object Large parts Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof Large parts-Trunk lid
640 images 82 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand and search unstructured image data * use active learning to improve your dataset over time 19 20 21 22 23 24 25 26 27 28 29 30
by companyname
306 images 84 classes
object Large parts Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof Large parts-Trunk lid
by companyname
1569 images 84 classes
object 81 82 Large parts-Front bumper Large parts-Front left door Large parts-Front left wheel Large parts-Front left wing Large parts-Front right door Large parts-Front right wheel Large parts-Front right wing Large parts-Hood Large parts-Rear body glass Large parts-Rear bumper Large parts-Rear left door Large parts-Rear left wheel Large parts-Rear left wing Large parts-Rear right door Large parts-Rear right wheel Large parts-Rear right wing Large parts-Roof