Face Recognition Model Initialization and Transmission for Storage Optimization
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Solution Overview
Problem
Existing face recognition technologies face inefficiencies due to the large storage space requirements of face recognition models, leading to excessive resource consumption and reduced processing efficiency in operation environments with limited storage capacity.
Innovation Solution
The method involves storing the face recognition model in a first operation environment with greater storage space, initializing it, and then transmitting the initialized model to a second operation environment with lesser storage space, allowing for efficient processing and reducing resource occupancy in the second environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the face recognition model is stored and initialized in the second operation environment with limited storage space, then the processing can be performed directly, but the storage space requirement exceeds the available capacity
Solution Approach 1:
The system divides the operation environment into two segments: a first operation environment with sufficient storage space for holding the complete face recognition model, and a second operation environment with limited storage space for execution. The model is segmented in terms of storage location versus execution location, allowing the heavy model data to reside in the first environment while only essential execution components are placed in the second environment.
Solution Approach 2:
A data transmission mechanism acts as an intermediary between the first and second operation environments. The initialized model data is transmitted from the first environment to the second environment through this intermediary channel, enabling the second environment to access and execute the model without permanently storing the complete model data, thus resolving the storage capacity conflict.
2Volume of stationary object
If the face recognition model is kept in the first operation environment with greater storage space, then storage capacity is sufficient, but processing efficiency decreases due to data transmission requirements
Solution Approach 1:
The system performs preliminary initialization of the face recognition model in the first operation environment before transmission to the second operation environment. By pre-processing and initializing the model data in advance in the first environment, the system reduces the complexity and time required for data transmission and setup in the second environment, thereby improving overall processing efficiency.
3Device complexity
If the face recognition model is transmitted to the second operation environment without initialization, then transmission is simpler, but additional initialization steps are required in the second environment increasing complexity
Solution Approach 1:
The initialization operation is moved to the first operation environment and performed before transmission to the second environment. This preliminary action ensures that the model data is fully prepared and initialized in advance, so that when it is transmitted to the second operation environment, no additional initialization steps are required there, thereby simplifying the overall operation process and reducing complexity.
Data Source
AI summary
A method and an apparatus for processing data, and a non-transitory computer readable storage medium. The method includes: obtaining a face recognition model stored in a first operation environment; performing an initialization on the face recognition model in the first operation environment, and transmitting the face recognition model subjected to the initialization to a second operation environment for storing, in which, a storage space in the first operation environment is greater than a storage space in the second operation environment.