Global 3D Maps | Spatial Models Training Data | 125K Locations | Machine Learning Data | 35TB Raw Images

#	uuid	dataset_uuid	sequence_name	sequence_number	device_os	device_name	geo_country_gps	geo_city_gps	geo_latitude_gps	geo_longitude_gps	geo_accuracy_gps	h3_12_gps	timestamp	timestamp_gps_timezone	orientation_rot_w	orientation_rot_x	orientation_rot_y	orientation_rot_z	position_pos_x	position_pos_y	position_pos_z	sfm_rot_w	sfm_rot_x	sfm_rot_y	sfm_rot_z	sfm_pos_x	sfm_pos_y	sfm_pos_z	xr_camera_intrinsics_focal_length_x	xr_camera_intrinsics_focal_length_y	xr_camera_intrinsics_resolution_x	xr_camera_intrinsics_resolution_y	xr_camera_intrinsics_principal_point_x	xr_camera_intrinsics_principal_point_y	compass_heading	compass_accuracy	compass_magnetic	satellite_view	satellite_used	speed_meters_per_second	input_acceleration_x	input_acceleration_y	input_acceleration_z	gyro_user_acceleration_x	gyro_user_acceleration_y	gyro_user_acceleration_z	ar_foundation_camera_stats_main_ar_foundation_current_speed	ar_foundation_camera_stats_main_ar_foundation_current_angle_speed	ar_foundation_camera_stats_main_ar_foundation_time_range_average	ar_foundation_camera_stats_main_ar_foundation_in_time_range_average_speed	ar_foundation_camera_stats_main_ar_foundation_in_time_range_average_angle_speed	ar_foundation_light_manager_main_last_intensity	light_estimation_data_average_brightness	light_estimation_data_average_color_temperature	light_estimation_data_color_correction_value_r	light_estimation_data_color_correction_value_g	light_estimation_data_color_correction_value_b	light_estimation_data_average_intensity_in_lumens	light_estimation_data_main_light_intensity_lumens	light_estimation_data_average_main_light_brightness	last_frame_event_args_exposure_duration	last_frame_event_args_exposure_offset	application_version	application_build_guid	exif_aperture_value	exif_brightness	exif_exposure_time	exif_shutter_speed	exif_exposure_bias	exif_f_number	exif_focal_length	exif_flash	exif_color_space	exif_photographic_sensitivity	exif_metering_mode	depth_camera_configured_depth_sensor_support	depth_last_rgb_width	depth_last_rgb_height	depth_last_depth_width	depth_last_depth_height	depth_last_depth_confidence_width	depth_last_depth_confidence_height	depth_last_depth_raw_width	depth_last_depth_raw_height	depth_last_depth_smoothed_width	depth_last_depth_smoothed_height	depth_last_human_depth_width	depth_last_human_depth_height	depth_last_human_stencil_width	depth_last_human_stencil_height	dataset_images_number	dataset_images_rgb_byte_size	dataset_images_depth_byte_size	dataset_timestamp_first_image	dataset_timestamp_last_image	dataset_h3_12_declared	dataset_h3_12_gps_avg	dataset_h3_12_gps_first_image	dataset_h3_12_gps_last_image	dataset_geo_country_gps_avg	dataset_geo_city_gps_avg	dataset_geo_latitude_gps_avg	dataset_geo_longitude_gps_avg	dataset_geo_accuracy_gps_avg	dataset_geo_accuracy_gps_median
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Volume

60M

Images and Metadata

Avail. Formats

.bin, .json, and .csv

File

Coverage

250

Countries

History

months

[Sample] 3D_Maps_sample_dataset.csv

Attribute	Type	Example
uuid	String	80bb696a-3b44-47ff-acbf-b4c180a96ebb_1_0000
dataset_uuid	String	80bb696a-3b44-47ff-acbf-b4c180a96ebb
sequence_name	Integer	10000
sequence_number	Integer	0
device_os	String	ios
device_name	String	iPhone15,4
geo_country_gps	String	Italy
geo_city_gps	String	Udine
geo_latitude_gps	Float	46.06332
geo_longitude_gps	Float	13.2356424
geo_accuracy_gps	Float	27.0
h3_12_gps	Integer	631043095217792511
timestamp	String	2025-05-21 07:36:50 UTC
timestamp_gps_timezone	String	Europe - Athens
orientation_rot_w	Float	0.2876765
orientation_rot_x	Float	0.05723609
orientation_rot_y	Float	-0.9446321
orientation_rot_z	Float	0.1470938
position_pos_x	Float	2.007549
position_pos_y	Float	1.190128
position_pos_z	Float	2.880159
sfm_rot_w	Float
sfm_rot_x	Float
sfm_rot_y	Float
sfm_rot_z	Float
sfm_pos_x	Float
sfm_pos_y	Float
sfm_pos_z	Float
xr_camera_intrinsics_focal_length_x	Float	2737.746
xr_camera_intrinsics_focal_length_y	Float	2737.746
xr_camera_intrinsics_resolution_x	Integer	3840
xr_camera_intrinsics_resolution_y	Integer	2160
xr_camera_intrinsics_principal_point_x	Float	1912.398
xr_camera_intrinsics_principal_point_y	Float	1086.938
compass_heading	Float	200.7714
compass_accuracy	Float	11.27206
compass_magnetic	Float	193.0363
satellite_view	Integer
satellite_used	Integer
speed_meters_per_second	Float
input_acceleration_x	Float	-0.03260803
input_acceleration_y	Float	-0.9468536
input_acceleration_z	Float	-0.3839569
gyro_user_acceleration_x	Float	-0.05825843
gyro_user_acceleration_y	Float	0.006068945
gyro_user_acceleration_z	Float	-0.08283016
ar_foundation_camera_stats_main_ar_foundation_current_speed	Float	0.4792112
ar_foundation_camera_stats_main_ar_foundation_current_angle_speed	Float	8.661532
ar_foundation_camera_stats_main_ar_foundation_time_range_average	Float	1.0
ar_foundation_camera_stats_main_ar_foundation_in_time_range_average_speed	Float	0.4002476
ar_foundation_camera_stats_main_ar_foundation_in_time_range_average_angle_speed	Float	13.75465
ar_foundation_light_manager_main_last_intensity	Float	1.160006
light_estimation_data_average_brightness	Float	0.5405627
light_estimation_data_average_color_temperature	Float	5784.545
light_estimation_data_color_correction_value_r	Float	0.0
light_estimation_data_color_correction_value_g	Float	0.0
light_estimation_data_color_correction_value_b	Float	0.0
light_estimation_data_average_intensity_in_lumens	Float	1081.125
light_estimation_data_main_light_intensity_lumens	Float	0.0
light_estimation_data_average_main_light_brightness	Float	0.0
last_frame_event_args_exposure_duration	Float	0.0166666666666667
last_frame_event_args_exposure_offset	Float	0.0937782
application_version	String	v1.6.9
application_build_guid	String	b8646ddd53d5c457187e7afa403b9213e
exif_aperture_value	Float	1.35614381022528
exif_brightness	Float	4.23416727686798
exif_exposure_time	Float	0.0166666666666667
exif_shutter_speed	Float	5.90798746070115
exif_exposure_bias	Float	0.0
exif_f_number	Float	1.6
exif_focal_length	Float	5.96
exif_flash	Boolean	f
exif_color_space	String	sRGB
exif_photographic_sensitivity	Integer	40
exif_metering_mode	String	Pattern
depth_camera_configured_depth_sensor_support	Boolean	t
depth_last_rgb_width	Integer	3840
depth_last_rgb_height	Integer	2160
depth_last_depth_width	String
depth_last_depth_height	String
depth_last_depth_confidence_width	String
depth_last_depth_confidence_height	String
depth_last_depth_raw_width	String
depth_last_depth_raw_height	String
depth_last_depth_smoothed_width	String
depth_last_depth_smoothed_height	String
depth_last_human_depth_width	Integer	256
depth_last_human_depth_height	Integer	144
depth_last_human_stencil_width	Integer	256
depth_last_human_stencil_height	Integer	144
dataset_images_number	Integer	1200
dataset_images_rgb_byte_size	Integer	3237532078
dataset_images_depth_byte_size	Integer	1835095
dataset_timestamp_first_image	String	2025-05-21 07:36:50 UTC
dataset_timestamp_last_image	String	2025-05-21 07:42:19 UTC
dataset_h3_12_declared	Integer	631043095256282111
dataset_h3_12_gps_avg	Integer	631043095256282111
dataset_h3_12_gps_first_image	Integer	631043095217792511
dataset_h3_12_gps_last_image	Integer	631043095256281599
dataset_geo_country_gps_avg	String	Italy
dataset_geo_city_gps_avg	String	Udine
dataset_geo_latitude_gps_avg	Float	46.063405431916664
dataset_geo_longitude_gps_avg	Float	13.235469743
dataset_geo_accuracy_gps_avg	Float	25.671666666666667
dataset_geo_accuracy_gps_median	Float	24.0

Comprehensive global 3D Maps dataset with 58 Mln smartphone-captured images including depth, poses, and Exif metadata, across 125K diverse locations. Ideal for Geospatial and Vision AI Models Training.

Our dataset delivers unprecedented scale and diversity for geospatial AI training: 🌍 Massive scale: 125,000 unique 3D map sequences and locations, 57,500,000 images, 35 TB of Data, orders of magnitude larger than datasets currently used for SOTA Vision/Spatial Models. ⏱️ Constantly growing dataset: 12k new 3D Map sequences and locations monthly. 📷 Full-frame, high-res captures: OVER retains full-resolution, dynamic aspect-ratio images with complete Exif metadata (GPS, timestamp, device orientation), multiple resolutions 1920x1080 - 3840x2880, pre-computed COLMAP poses. 🧭 Global diversity: Environments span urban, suburban, rural, and natural settings across 120+ countries, capturing architectural, infrastructural, and environmental variety. 📐 Rich metadata: Per-image geolocation (±3 m accuracy), timestamps, device pose, COLMAP pose; per-map calibration data (camera intrinsics/extrinsics). 🧠 Applications: Spatial Models Training, Multi-view stereo & NeRF/3DGS training, semantic segmentation, novel view synthesis, 3D object detection, geolocation, urban planning, AR/VR, autonomous navigation.

Africa (58)

Algeria

Angola

Benin

Botswana

Burkina Faso

Burundi

Cabo Verde

Cameroon

Central African Republic

Chad

Comoros

Congo

Congo (Democratic Republic of the)

Côte d'Ivoire

Djibouti

Egypt

Equatorial Guinea

Eritrea

Ethiopia

Gabon

Gambia

Ghana

Guinea

Guinea-Bissau

Kenya

Lesotho

Liberia

Libya

Madagascar

Malawi

Mali

Mauritania

Mauritius

Mayotte

Morocco

Mozambique

Namibia

Niger

Nigeria

Rwanda

Réunion

Saint Helena, Ascension and Tristan da Cunha

Sao Tome and Principe

Senegal

Seychelles

Sierra Leone

Somalia

South Africa

South Sudan

Sudan

Swaziland

Tanzania, United Republic of

Togo

Tunisia

Uganda

Western Sahara

Zambia

Zimbabwe

Asia (51)

Afghanistan

Armenia

Azerbaijan

Bahrain

Bangladesh

Bhutan

Brunei Darussalam

Cambodia

China

Cyprus

Georgia

Hong Kong

India

Indonesia

Iran (Islamic Republic of)

Iraq

Israel

Japan

Jordan

Kazakhstan

Korea (Democratic People's Republic of)

Korea (Republic of)

Kuwait

Kyrgyzstan

Lao People's Democratic Republic

Lebanon

Macao

Malaysia

Maldives

Mongolia

Myanmar

Nepal

Oman

Pakistan

Palestine, State of

Philippines

Qatar

Saudi Arabia

Singapore

Sri Lanka

Syrian Arab Republic

Taiwan

Tajikistan

Thailand

Timor-Leste

Turkey

Turkmenistan

United Arab Emirates

Uzbekistan

Vietnam

Yemen

Europe (52)

Albania

Andorra

Austria

Belarus

Belgium

Bosnia and Herzegovina

Bulgaria

Croatia

Czech Republic

Denmark

Estonia

Faroe Islands

Finland

France

Germany

Gibraltar

Greece

Guernsey

Holy See

Hungary

Iceland

Ireland

Isle of Man

Italy

Jersey

Kosovo

Latvia

Liechtenstein

Lithuania

Luxembourg

Macedonia (the former Yugoslav Republic of)

Malta

Moldova (Republic of)

Monaco

Montenegro

Netherlands

Norway

Poland

Portugal

Romania

Russian Federation

San Marino

Serbia

Slovakia

Slovenia

Spain

Svalbard and Jan Mayen

Sweden

Switzerland

Ukraine

United Kingdom

Åland Islands

North America (13)

Belize

Bermuda

Canada

Costa Rica

El Salvador

Greenland

Guatemala

Honduras

Mexico

Nicaragua

Panama

Saint Pierre and Miquelon

United States of America

Oceania (25)

American Samoa

Australia

Cook Islands

Fiji

French Polynesia

Guam

Kiribati

Marshall Islands

Micronesia (Federated States of)

Nauru

New Caledonia

New Zealand

Niue

Norfolk Island

Northern Mariana Islands

Palau

Papua New Guinea

Pitcairn

Samoa

Solomon Islands

Tokelau

Tonga

Tuvalu

Vanuatu

Wallis and Futuna

Other (9)

Antarctica

Bouvet Island

British Indian Ocean Territory

Christmas Island

Cocos (Keeling) Islands

French Southern Territories

Heard Island and McDonald Islands

South Georgia and the South Sandwich Islands

United States Minor Outlying Islands

South America (42)

Anguilla

Antigua and Barbuda

Argentina

Aruba

Bahamas

Barbados

Bolivia (Plurinational State of)

Bonaire, Sint Eustatius and Saba

Brazil

Cayman Islands

Chile

Colombia

Cuba

Curaçao

Dominica

Dominican Republic

Ecuador

Falkland Islands (Malvinas)

French Guiana

Grenada

Guadeloupe

Guyana

Haiti

Jamaica

Martinique

Montserrat

Paraguay

Peru

Puerto Rico

Saint Barthélemy

Saint Kitts and Nevis

Saint Lucia

Saint Martin (French part)

Saint Vincent and the Grenadines

Sint Maarten (Dutch part)

Suriname

Trinidad and Tobago

Turks and Caicos Islands

Uruguay

Venezuela (Bolivarian Republic of)

Virgin Islands (British)

Virgin Islands (U.S.)

24 months of historical data

125,000	3D Maps and Locations
60 million	Images and Metadata
35	TB of Raw Data

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Not available
Usage-based	$2.50 / Per 3D Map

Request detailed pricing

Methods

Frequency

Format

Artificial Intelligence (AI) Deep Learning Earth Observation

Autonomous Driving

Location Visualization

Map Data GIS Data Geographic Data Machine Learning (ML) Data Computer Vision Data

global location apis

57.5M Images and Metadata

250 countries covered

24 months of historical data

Comprehensive global 3D Maps dataset with 58 Mln smartphone-captured images including depth, poses, and Exif metadata, across 125 K diverse locations. Comput...

230M Locations Included

100% Open Web Data

249 countries covered

Access 230M+ global POIs enriched with geographic coordinates, location names, and map-friendly metadata. Ideal for GIS, mapping, and spatial analysis - deli...

131B Monthly Location Pings

99% Horizontal Accuracy

249 countries covered

We provide high-quality persistent mobility data from our partnered mobile apps & SDKs and this data feed is aggregated from multiple data sources globally a...

2M image records

250 countries covered

10 years of historical data

A comprehensive dataset of 2M+ architecture images sourced globally, featuring full EXIF data, including camera settings and photography details. Enriched wi...

What is Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images?

What is Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images used for?

This product has 5 key use cases. Over The Reality recommends using the data for Artificial Intelligence (AI), Deep Learning, Earth Observation, Autonomous Driving, and Location Visualization. Global businesses and organizations buy Map Data from Over The Reality to fuel their analytics and enrichment.

Who can use Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images?

This product is best suited if you’re a Enterprise looking for Map Data. Get in touch with Over The Reality to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images go?

This product has 24 months of historical coverage. It can be delivered on a monthly basis.

Which countries does Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images cover?

This product includes data covering 250 countries like USA, China, Japan, Germany, and India. Over The Reality is headquartered in Italy.

How much does Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images cost?

Pricing for Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images starts at USD2.50 per Per 3D Map. Connect with Over The Reality to get a quote and arrange custom pricing models based on your data requirements.

How can I get Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images?

Businesses can buy Map Data from Over The Reality and get the data via SFTP and REST API. Depending on your data requirements and subscription budget, Over The Reality can deliver this product in .bin, .json, and .csv format.

What is the data quality of Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images?

You can compare and assess the data quality of Over The Reality using Datarade’s data marketplace.

What are similar products to Global 3D Maps Spatial Models Training Data 125K Locations Machine Learning Data 35TB Raw Images?

This product has 3 related products. These alternatives include Computer Vision Data 3D Maps 125k Global Locations 60M Images SLAM COLMAP Depth, Global Geospatial & GIS Data 230M+ POIs with Location Coordinates, Mapping Metadata & 5000 Categories, and Factori AI & ML Training Data Mobility Data Global Machine Learning Data Carrier, IP address, Hex8, Hex9 Historical Location data. You can compare the best Map Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Starts at

$2.50 / Per 3D Map

License	Starts at
One-off purchase	Not available
Monthly License	Not available
Yearly License	Not available
Usage-based	$2.50 / Per 3D Map

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Global 3D Maps | Spatial Models Training Data | 125K Locations | Machine Learning Data | 35TB Raw Images

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

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Frequently asked questions

Over The Reality
The future of spatial computing

Global 3D Maps | Spatial Models Training Data | 125K Locations | Machine Learning Data | 35TB Raw Images

Data Dictionary

Description

Country Coverage

History

Volume

Pricing

Suitable Company Sizes

Delivery

Use Cases

Categories

Related Searches

Related Products

Frequently asked questions

Over The Reality The future of spatial computing

Over The Reality
The future of spatial computing