Milk Powder Baby Products Occluded Image Dataset

#image segmentation #object detection #object recognition #image classification #retail analysis
  • 15000 records
  • 3.6G
  • JPG/PNG/JSON
  • CATL
  • MOBIUSI INCMOBIUSI INC
Updated:2026-04-16

AI Analysis & Value Prop

The retail e-commerce sector is currently facing challenges with effective product recognition due to occlusion in images, which can significantly hinder the customer experience. Existing solutions often rely on non-occluded images, limiting their effectiveness in real-world scenarios. This dataset aims to address the specific technical problem of identifying and classifying occluded baby product images, fulfilling the business need for enhanced image recognition capabilities in e-commerce. The dataset comprises images collected from various retail environments using high-resolution cameras, ensuring diverse occlusion scenarios. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high accuracy. Data is stored in JPG format, organized into folders by category, and includes metadata files for easy access and processing.

Dataset Insights

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Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
image_brightnessfloatThe overall brightness value of the image, used to determine the lighting conditions of the image.
image_contrastfloatThe contrast value of the image reflects the difference between light and dark.
number_of_objectsintThe number of specific commodity targets detected in the image.
occlusion_levelfloatThe extent to which products are blocked in the image, ranging from 0 to 1.
dominant_colorstringThe dominant color in the image.
sharpnessfloatThe sharpness measurement of the image.
noise_levelfloatThe noise level in the image, indicating the quality of the image.
angle_of_viewintThe horizontal viewing angle of the camera when capturing the image.
background_complexityintThe complexity of the background in the image, affecting the difficulty of target recognition.
focus_depthfloatThe depth of field range of the image, affecting the clear display of the product.

Compliance Statement

Authorization TypeProprietary - Commercial AI Training License (No Redistribution)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What is the milk powder and maternal-infant product occlusion recognition image dataset?
The milk powder and maternal-infant product occlusion recognition image dataset is a target detection dataset focused on identifying milk powder and maternal-infant products that are partially obscured by other objects.
Which industry is this dataset mainly used for?
This dataset is mainly used in the retail industry to help improve the accuracy of product recognition.
What are the characteristics of the images in the dataset?
The images in the dataset feature occluded milk powder and maternal-infant products, which can be used to train models to better recognize obscured items.
Why is occlusion recognition of milk powder and maternal-infant products needed?
Recognizing occluded milk powder and maternal-infant products can improve the efficiency of automated inventory management and product display in stores.
How to use this dataset for machine learning model training?
The occluded images in the dataset can be used as input to train object detection algorithms, enhancing the model's recognition capabilities in complex scenes.

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Cite this Work

@dataset{Mobiusi2025,
  title={Milk Powder Baby Products Occluded Image Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/f53b852b2ffcb84b8312b2f8d279c0ef?dataset_scene_id=9},
  urldate={2025-08-28},
  keywords={milk powder dataset,baby products image dataset,occluded images,retail e-commerce dataset},
  version={1.0}
}

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