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Top Language Datasets and Models
The datasets below can be used to train fine-tuned models for language 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 language datasets below.
by Steven Kuo
1680 images 821 classes
Arch-Category_Analytics Arch-Category_Application-Integration Arch-Category_Blockchain Arch-Category_Business-Applications Arch-Category_Cloud-Financial-Management Arch-Category_Compute Arch-Category_Containers Arch-Category_Customer-Enablement Arch-Category_Database Arch-Category_Developer-Tools Arch-Category_End-User-Computing Arch-Category_Front-End-Web-Mobile Arch-Category_Games Arch-Category_Internet-of-Things Arch-Category_Management-Governance Arch-Category_Media-Services Arch-Category_Migration-Transfer Arch-Category_Networking-Content-Delivery Arch-Category_Quantum-Technologies Arch-Category_Robotics
by Amine
50 images 9 classes
by dhruti
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) 15 16 17 18 19 20 21 22 23 24 25 ==============================
320 images 15 classes
by Laxav
1800 images 27 classes
* Auto-orientation of pixel data (with EXIF-orientation stripping) * 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 and search unstructured image data * use active learning to improve your dataset over time 0 13 16 18 21 25 3 5 ============================== A American Sign Language Letters - v1 v1 For state of the art Computer Vision training notebooks you can use with this dataset,
by citrus
92 images 15 classes
1 - See-through register in denominational numeral- 1-BG - Year of printing of the note on left 10 - Ashoka pillar emblem on the right- 11 -Circle with Rs 500 in raised print on the right- 12 -Five bleed lines on left and right in raised print- 2 - Latent image of the denomination numeral- 2-BG - Swachh Bharat logo with the slogan- 3 - Denomination numeral in Devnagari- 3-BG - Language panel towards the centre- 4 - Mahatma Gandhi-s portrait in centre facing to right- 4 -BG- Red Fort with Indian flag- 5 - Windowed security thread that changes colours from green to blue when the note is tilted- 5-BG - Denomination numeral in Devnagari on right- 6 - Guarantee clauseGovernor-s signature with promise clause and RBI emblem tilted towards the right 9 - Denomination in numerals with rupee symbol in colour changing ink -green to blue- on the bottom right-
40 images 40 classes
AI Platform App Engine Artifact Registry BigQuery Cloud Bigtable Cloud CDN Cloud DNS Cloud Datastore Cloud Deployment Manager Cloud Endpoints Cloud Functions Cloud IAM Cloud Jobs API Cloud Load Balancing Cloud Natural Language API Cloud Network Cloud SQL Cloud Storage Cloud Tools for Powershell Cloud Translation API
by ML
227 images 2 classes
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 Amrutha
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
487 images 12 classes
2462 images 24 classes
625 images 13 classes
834 images 16 classes