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Enhance Gender Classification Task to in Real-time Using OpenCV and Transfer Learning #109

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sakrenu opened this issue May 26, 2024 · 4 comments
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@sakrenu
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sakrenu commented May 26, 2024

The current gender classification task is not operating in real-time, which limits its applicability in scenarios that require immediate feedback. This lack of real-time processing can be frustrating, especially in applications where timely responses are crucial.

I would like to enhance the gender classification task to function in real-time by integrating OpenCV for efficient video processing and utilizing transfer learning techniques to leverage pre-trained models. This approach should significantly reduce the processing time and enable the system to provide immediate gender classification results from live video feeds.

Optimizing Existing Model: Attempting to optimize the current model's architecture and parameters for faster inference without changing the underlying technology.
Using Other Libraries: Considering other computer vision libraries or frameworks that might offer better real-time processing capabilities.
Hardware Acceleration: Exploring the use of hardware accelerators like GPUs or TPUs to improve the real-time performance of the current setup.

So please assign me this task .

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Hi there! Thanks for opening this issue. We appreciate your contribution to this open-source project. We aim to respond or assign your issue as soon as possible.

@sakrenu
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sakrenu commented May 26, 2024 via email

@TAHIR0110
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@sakrenu assigned!

@TAHIR0110 TAHIR0110 added gssoc Associated with GSSOC level2 labels May 26, 2024
@aryanchauh
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@TAHIR0110 sir!
Can I work on this kind of issue . I have made real time hand sign detection . Can u
Assign me this issue please sir

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