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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.
1240 images 706 classes
by FYP Apai
268 images 15 classes
9880 images 525 classes
ABBOTTS BABBLER ABBOTTS BOOBY ABYSSINIAN GROUND HORNBILL AFRICAN CROWNED CRANE AFRICAN EMERALD CUCKOO AFRICAN FIREFINCH AFRICAN OYSTER CATCHER AFRICAN PIED HORNBILL AFRICAN PYGMY GOOSE ALBATROSS ALBERTS TOWHEE ALEXANDRINE PARAKEET ALPINE CHOUGH ALTAMIRA YELLOWTHROAT AMERICAN AVOCET AMERICAN BITTERN AMERICAN COOT AMERICAN DIPPER AMERICAN FLAMINGO AMERICAN GOLDFINCH
by tara
5228 images 6 classes
3345 images 525 classes
ABBOTTS BABBLER ABBOTTS BOOBY ABYSSINIAN GROUND HORNBILL AFRICAN CROWNED CRANE AFRICAN EMERALD CUCKOO AFRICAN FIREFINCH AFRICAN OYSTER CATCHER AFRICAN PIED HORNBILL AFRICAN PYGMY GOOSE ALBATROSS ALBERTS TOWHEE ALEXANDRINE PARAKEET ALPINE CHOUGH ALTAMIRA YELLOWTHROAT AMERICAN AVOCET AMERICAN BITTERN AMERICAN COOT AMERICAN DIPPER AMERICAN FLAMINGO AMERICAN GOLDFINCH
by eg
8343 images 313 classes
6_October_Bridge Abdeen_Palace Abu_Ghurab Abu_Haggag_Mosque Abu_Qir_Bay Abu_el-Abbas_el-Mursi_Mosque Agiba_beach Aguilkia_Island Ahmed_Shawki_Museum Akhenaten Al-Aqmar_Mosque Al-Ashraf_Mosque Al-Azhar_Park_(Cairo) Al-Fath_Mosque Al-Ghuri_Complex Al-Jawhara_Palace_museum Al-Manyal_Palace_Museum Al-Nur_Mosque Al-Qurn Al-Rifa'i_Mosque
382 images 6 classes
1192 images 8 classes
by Daniel Flint
800 images 29 classes
wood a completed and engraved end-grain board a completed end-grain board a completed urn a compolated and engraved urn a finished and engraved end-grain board a finished and engraved urn a finished end-grain board a finished urn applying the finish to an end-grain board assembeling an end-grain board assembeling an urn cutting splines on an urn using a table-saw cutting wood using a miter-saw end-grain blanks end-grain blanks cut and flipped on end end-grain blanks glued and clamped flatening the top of an end-grain board using a router-jig laser-engraving an end-grain board laser-engraving an urn
by ElDoradooo
6675 images 36 classes
2162 images 69 classes
1-U-turn 10-No-entry 11-Weight-limit-sign-5T 12-Weight-limit-sign-30T 13-Height-limit-sign-2.0m 14-Height-limit-sign-3.0m 15-Height-limit-sign-4.0m 16-Height-limit-sign-5.0m 17-Height-limit-sign-6.0m 18-Speed-Limit-20 19-Speed-Limit-30 2-Keep-right 21-Speed-Limit-50 22-Speed-Limit-60 23-Speed-Limit-70 24-Speed-Limit-80 25-Speed-Limit-90 26-Speed-Limit-110 27-No-Entry-for-Vehicles-Exceeding-5T 28-Heavy-vehicles-no-driving-on-the-right-lane
by Marco
9560 images 52 classes
* 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down * Random Gaussian blur of between 0 and 1.75 pixels * Random brigthness adjustment of between -25 and +25 percent * Random exposure adjustment of between -15 and +15 percent * Random rotation of between -10 and +10 degrees * Random shear of between -2° to +2° horizontally and -2° to +2° vertically * Randomly crop between 0 and 15 percent of the image * Resize to 640x640 (Stretch) * Salt and pepper noise was applied to 2 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 29 30
by Daniel Flint
784 images 28 classes
a completed and engraved end-grain board a completed end-grain board a completed urn a compolated and engraved urn a finished and engraved end-grain board a finished and engraved urn a finished end-grain board a finished urn applying the finish to an end-grain board assembeling an end-grain board assembeling an urn cutting splines on an urn using a table-saw cutting wood using a miter-saw end-grain blanks end-grain blanks cut and flipped on end end-grain blanks glued and clamped flatening the top of an end-grain board using a router-jig laser-engraving an end-grain board laser-engraving an urn planning an end-grain blank using a planner
3785 images 41 classes
speaker 24V-power-cord acousto-optic-alarm area-display bus-isolation-module coded-smoke-detector coded-temperature-detector dedicated-metal-module-box-for-fire-pump dedicated-metal-module-box-for-fire-smoke-exhaust-fan dedicated-metal-module-box-for-fire-supplementary-fan deflation-indicator-light electrical-fire-monitoring-line emergency-manual-start-stop-button explosion-proof-smoke-detector fire-broadcasting-line fire-equipment-power-monitoring-line fire-fan-manual-control-line fire-hydrant-button fire-telephone-extension fire-water-pump-manual-control-line
by Daniel Flint
1042 images 26 classes
applying the finish to an end-grain board assembeling an end-grain board assembeling an urn completed and engraved end-grain board completed end-grain board completed urn compolated and engraved urn cutting splines on an urn using a table-saw cutting wood using a miter-saw end-grain blanks end-grain blanks glued and clamped finished and engraved urn finished end-grain board finished urn flatening the top of an end-grain board using a router-jig laser-engraving an end-grain board laser-engraving an urn planning an end-grain blank using a planner routering the edges of an end-grain board using a router-table routering the edges of an urn using a router-table
by bk
77 images 71 classes
Colorway: 0w0 Colorway: 420 Colorway: ACES Colorway: Amethyst Colorway: Aquamarine Colorway: Balldrop Colorway: Blue Showers Colorway: C-Eye-Ber Monday (B) Colorway: C-Eye-Ber Monday (R) Colorway: C-Eye-Ber-Monday (G) Colorway: C-O-L-D Colorway: Candy Colorway: Clockwork Blue Colorway: Clockwork Orange Colorway: Crush Colorway: Deep Space Colorway: Diamond Colorway: Emerald Colorway: Fruit Water Colorway: Garnet
by MyDatas
18280 images 23 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 ============================== For state of the art Computer Vision training notebooks you can use with this dataset, No image augmentation techniques were applied. Roboflow is an end-to-end computer vision platform that helps you The dataset includes 18310 images. The following pre-processing was applied to each image: Thing are annotated in YOLOv8 format. This dataset was exported via roboflow.com on May 8, 2024 at 8:52 PM GMT
1720 images 26 classes
* 50% probability of horizontal flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Random Gaussian blur of between 0 and 1.25 pixels * Random brigthness adjustment of between -25 and +25 percent * Random rotation of between -5 and +5 degrees * Random shear of between -5° to +5° horizontally and -5° to +5° vertically * Randomly crop between 0 and 20 percent of the image * Resize to 416x416 (Stretch) * annotate, and create datasets * collaborate with your team on computer vision projects * collect & organize images * export, train, and deploy computer vision models * understand unstructured image data * use active learning to improve your dataset over time 22 23 24 25 ============================== American Sign Language Letters - v1 v1
by AI
2240 images 34 classes
object * 50% probability of horizontal flip * 50% probability of vertical flip * Auto-orientation of pixel data (with EXIF-orientation stripping) * Resize to 640x640 (Stretch) * annotate, and create datasets * annotate, and create datasets * collect & organize images * annotate, and create datasets * understand and search unstructured image data * 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 23 24 24 25 26