Related Objects of Interest: ford f-series, honda civic, honda cr-v, hyundai elantra, kia rio, ram 1500-2500-3500, toyota corrola, toyota rav4, chevrolet silverado, toyota tacoma
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Top 2500 Datasets and Models
The datasets below can be used to train fine-tuned models for 2500 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 2500 datasets below.
by phrontlyne
8109 images 375 classes
$ 196 1992Geo Metro LSi 1994 1999 Dodge Caravan 2006 Dodge Charger SRT8 2008 BMW X5 2008 2009 BMW 650i 2010 BMW 328i 2012 Jeep Wrangler Rubicon 2014 Ford E-350 2016 Toyota Sequoia Acura Integra GS-R 2000 Acura Integra Type R 2001 Acura Integra Type-R Acura RL Sedan 2012 Acura TL Sedan 2012 Acura TL Type S Navigation 2007 Acura TL Type-S 2008 Acura TSX Sedan 2012
by sanu
87 images 496 classes
pipe yellow (1") CPVC PRO 45 DEG ELBOW (1") CPVC PRO COUPLER SDR 11 (1") CPVC PRO F.A.P.T SDR 11 (1") CPVC PRO PIPE CTS SDR11 5M (1") CPVC PRO TEE SDR 11 (1-1/4") CPVC PRO 45 DEG ELBOW (1-1/4") CPVC PRO 90 DEG ELBOW (1-1/4") CPVC PRO COUPLER SDR 11 (1-1/4") CPVC PRO F.A.P.T SDR 11 (1-1/4") CPVC PRO PIPE CTS SDR 11 5M (1-1/4") CPVC PRO TEE SDR 11 (1-1/4"x1") CPVC PRO COUPLER SDR 11 (1-1/4"x1") CPVC PRO TEE SDR 11 (3/4") CPVC PRO M.A.B.T SDR 11 (3/4") CPVC PRO PIPE CTS SDR 11 5M (3/4"x1/2") CPVC PRO BRS FPT 90 ELB (3/4"x1/2") CPVC PRO BRS FPT TEE SDR 11 (Brass)
707 images 68 classes
Acura MDX 2016 Audi TT 2016 Chevrolet Colorado 2016 Chevrolet Cruze 2016 Chevrolet Express 2016 Chevrolet Malibu 2016 Chevrolet S10 2016 Chevrolet Silverado 2016 Chevrolet Sonic 2016 Chevrolet Tahoe 2016 Dodge Challenger 2016 Dodge Journey 2016 Dodge Ram 1500 2016 Fiat 500 2016 Ford Escape 2016 Ford F150 2016 Ford F250 2016 Ford F350 2016 Ford Fiesta 2016 Ford Mustang 2016
8204 images 13197 classes
529 images 4201 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 100 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 101 1010
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