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Description

Capture images personally to fill in the gaps and contribute to a shared street-level perspective of the world by using any camera at your disposal. Enhance maps by incorporating details that cannot be seen from above, utilizing street-level photos from any necessary location. Accelerate the map updating process and reduce the required effort by leveraging features identified through computer vision technology. Facilitate access to data that empowers individuals to make informed choices regarding urban planning, traffic management, and self-driving technologies. Allow the public to easily obtain vital information and resources. Collaborate with various entities—including governmental organizations, researchers, and businesses—by sharing street-level imagery to foster progress and innovation. Make your previously gathered photos, video footage, or logs available to the public with the help of our user-friendly upload tools. Seek assistance for larger data imports and contribute to a more connected and informed community. By doing so, you can play a vital role in transforming how cities are perceived and navigated.

Description

Utilizing only real data presents notable obstacles in the training of machine learning models. In contrast, synthetic data offers boundless opportunities for training, effectively mitigating the limitations associated with real datasets. Enhance the efficacy of your geospatial analytics by generating the specific imagery you require. With customizable options for satellite, drone, and aerial images, you can swiftly and iteratively create various scenarios, modify object ratios, and fine-tune imaging parameters. This flexibility allows for the generation of any infrequent objects or events. The resulting datasets are meticulously annotated, devoid of errors, and primed for effective training. The OneView simulation engine constructs 3D environments that serve as the foundation for synthetic aerial and satellite imagery, incorporating numerous randomization elements, filters, and variable parameters. These synthetic visuals can effectively substitute real data in the training of machine learning models for remote sensing applications, leading to enhanced interpretation outcomes, particularly in situations where data coverage is sparse or quality is subpar. With the ability to customize and iterate quickly, users can tailor their datasets to meet specific project needs, further optimizing the training process.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

No details available.

Integrations

No details available.

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Mapillary

Founded

2013

Country

Sweden

Website

www.mapillary.com

Vendor Details

Company Name

OneView

Founded

2018

Country

Israel

Website

www.oneview.space/

Product Features

GIS

3D Imagery
Census Data Integration
Color Coding
Geocoding
Image Exporting
Image Management
Internet Mapping
Interoperability
Labeling
Map Creation
Map Sharing
Near-Matching
Reverse Geocoding
Spatial Analysis

Product Features

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