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file_name
stringclasses
5 values
quality
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3 values
object_count
stringclasses
4 values
main_object_type
stringclasses
3 values
main_object_color
stringclasses
3 values
lighting_condition
stringclasses
2 values
image_quality
stringclasses
2 values
background_complexity
stringclasses
3 values
object_position
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5 values
image_orientation
stringclasses
2 values
texture_pattern
stringclasses
3 values
object_distance
stringclasses
3 values
6457b6ee78d8f7ce03895764c9e6e8d3.jpg
1080*1371
2
Robot Vacuum
White
Bright
High Quality
Simple
Right
Portrait
Smooth
About 1 meter
9e6a8f8f1436bf9e349b11895054065f.jpg
1080*1440
multiple
robot dog
black and white
bright
high quality
complex
centered
portrait
various patterns
about 1 meter
b47b1d22d9db7e63db5e436e3662f360.jpg
1080*1920
5
robot vacuum
white
bright
high quality
simple
center
portrait
smooth
about 1 meter
e45d3010939e9e2d39f9bb336891a002.jpg
1080*1440
2
Robot Vacuum
White
Bright
High Quality
Simple
Bottom Left
Portrait
Smooth
About 2 meters
e6ff42cf5ac238d3d02a700415201b5c.jpg
1080*1440
1
Robot Vacuum
White
Bright
High Quality
Simple
Center
Portrait
Smooth
About 1 meter

Home Robot Image Classification Dataset

With the rapid development of smart devices, home robots are playing an increasingly important role in daily life. However, existing image recognition technology still lacks accuracy in complex environments, leading to misjudgments when robots recognize obstacles and execute tasks. This dataset aims to address the image classification issues of home robots in different scenes and provides high-quality labeled data for algorithm training. Data collection involved real shooting in various home scenarios, using high-resolution cameras to capture images under different lighting and environmental conditions. To ensure data quality, quality control measures such as multiple rounds of labeling, consistency checks, and expert reviews were used. The final storage is in JPG format, organized in a folder structure for easy subsequent use.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
object_count int The number of objects identified in the image.
main_object_type string The type of the main object in the image, such as chair, table, etc.
main_object_color string The color of the main object in the image.
lighting_condition string The lighting condition during image capture, such as bright, dim, etc.
image_quality string The clarity and noise level of the image, such as high quality, medium quality, etc.
background_complexity string The complexity of the image background, such as simple, complex, etc.
object_position string The position of the main object in the image, such as upper left, center, etc.
image_orientation string The orientation of the image, such as landscape, portrait, etc.
texture_pattern string The texture or pattern characteristics of the main object's surface in the image.
object_distance float The estimated distance between the camera and the main object in the image, in meters.

Compliance Statement

Authorization Type CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial Use Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization No PII, no real company names, simulated scenarios follow industry standards
Compliance System Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com

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