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shangzx/Amusement-Park-Game-Facility-Recognition-Image-Dataset

Amusement Park Game Facility Recognition Image Dataset In the retail e-commerce sector, as consumer demand for amusement park facilities increases, merchants face challenges in quickly identifying and managing various facilities. Existing image recognition technologies still lack in accuracy and speed, especially in scenarios with diverse facility combinations. This dataset aims to enhance the precision and efficiency of amusement park facility recognition, satisfying the… See the full description on the dataset page: https://huggingface.co/datasets/shangzx/Amusement-Park-Game-Facility-Recognition-Image-Dataset.

sourceHugging Facecc-by-nc-sa-4.0updated 7mo agoView on Hugging Face
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Dataset Card

Amusement Park Game Facility Recognition Image Dataset

In the retail e-commerce sector, as consumer demand for amusement park facilities increases, merchants face challenges in quickly identifying and managing various facilities. Existing image recognition technologies still lack in accuracy and speed, especially in scenarios with diverse facility combinations. This dataset aims to enhance the precision and efficiency of amusement park facility recognition, satisfying the business needs of online platforms for personalized recommendations and inventory management.The dataset was captured using high-resolution cameras in real amusement park environments, ensuring it includes different time periods and various lighting conditions during the collection process. It has undergone multiple rounds of expert annotation and consistency checks to ensure precise labeling, reviewed by a team with a computer vision background. The data preprocessing includes denoising, color correction, and geometric correction, and it is stored in JPG format, with a clear structure that is easy to access.The core advantage of this dataset lies in its high annotation precision and consistency, reaching over 95%, greatly enhancing model training efficacy. With innovative augmentation techniques, the model can better generalize to unseen data. In practical applications, it can effectively improve the accuracy of amusement facility recognition by more than 20%. Compared to similar datasets, it offers a richer variety of facilities and scene variability, making it particularly suitable for promotion on various e-commerce platforms. The dataset can be extended to more industry application scenarios and possesses strong versatility.

Technical Specifications

FieldTypeDescription
file_namestringFile name
qualitystringResolution
facility_typestringThe specific type of amusement park facility identified, such as carousel, bumper cars, etc.
facility_colorstringThe main color of the identified amusement park facility.
material_typestringThe main type of material of the amusement park facility, such as metal, plastic, etc.
age_rangestringThe age range suitable for users of the facility, such as children, teenagers, etc.
safety_featuresstringThe main safety features of the facility, such as seat belts, guard rails, etc.
capacityintThe maximum number of people the facility can accommodate.
manufacturerstringThe manufacturer of the facility.
usage_statusstringThe current usage status of the facility, such as operational, under maintenance, etc.

Compliance Statement

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

Source & Contact

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