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file_name
stringclasses
4 values
quality
stringclasses
4 values
shoe_type
stringclasses
2 values
shoe_color
stringclasses
4 values
shoe_brand
stringclasses
3 values
obstruction_level
stringclasses
2 values
background_scene
stringclasses
1 value
image_quality
stringclasses
2 values
lighting_condition
stringclasses
1 value
image_orientation
stringclasses
2 values
510cdcc0aad16499fe02685de872b0f8.jpg
1224*1632
Low
White and Orange
northwave
No Obstruction
Indoor Environment
HD
Bright
Front
63c30f1b88b300506d220170bf1bf286.jpg
1198*695
Low-top
Gray and Black, Pink Details
Unrecognizable
Unobstructed
Indoor Environment
High Definition
Bright
Upright
77f5bced1daaae705bd8e791426e8928.jpg
762*695
Low
Gray
Unidentifiable
No Obstruction
Indoor Environment
HD
Bright
Front
e46ae4369cb924b11356f17743bbdc10.jpg
788*1050
Low
Black and White
Unidentifiable
No Obstruction
Indoor Environment
HD
Bright
Front

Mountain Shoe Occlusion Image Dataset

The retail e-commerce sector is facing significant challenges due to the increasing complexity of product recognition in images affected by various occlusions, such as mud cover, grass camouflage, and motion blur. Existing solutions often struggle with accuracy and robustness, particularly under these challenging conditions. This dataset aims to address these specific technical issues by providing a rich source of images that depict mountain shoes under various occlusion scenarios, which are crucial for training more effective recognition models. The dataset has been compiled using high-resolution photography techniques in diverse outdoor environments, ensuring a variety of occlusion types. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews, ensuring high-quality labeled data. The data is stored in JPG format, organized in a structured manner for easy access and use.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
shoe_type string Identify the type of hiking shoes appearing in the image, such as low-cut, mid-cut, high-cut.
shoe_color string Identify the color of the hiking shoes in the image.
shoe_brand string Identify the brand of the hiking shoes in the image, if the trademark is visible.
obstruction_level string Identify the degree to which the hiking shoe in the image is obstructed, such as: no obstruction, partially obstructed, completely obstructed.
background_scene string Identify the background scene in which the hiking shoe is photographed, such as: outdoor mountainous area, indoor environment.
image_quality string The quality grade of the image, such as: high definition, blurry, low definition.
lighting_condition string Lighting conditions in the image, such as: bright, dim, backlit.
image_orientation string Identify the rotation direction of the image, such as: upright, 90 degrees left, 90 degrees right, inverted.

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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