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Machine learning desktop app with Python Programming - Keras Framework

***Budget is $40-60***

Fix in 1.5 days (Start immediately and give progress in every 2 hours)

Keras Framework

Its a project about sign language translator

Translate sign language into text

Actually I have done the project however when i tried to do the real-time video. The classification all when wrong but the accuracy is 100percent

Let say i do “good” sign but the output text is not “good” its something else

So i do not know what went wrong

Codes file: [login to view URL]

Model [login to view URL]: [login to view URL]

[login to view URL]

I follow this one

The sequential layer

But this one only for image so i am not sure about the image if captured from video with different background etc

What I assume that Model is highly overfitted that means it is trained on some unwanted data such as face, background, other colors etc. thats why it doesn't perform well on real time video

Now, to resolve this. Proposing a solution to first detect hands from the image, crop that hands part only and train & test the model only on that part of image with having applied contour

This may work to resolve the issue

ATTACHED research paper that I want to develop

This is what basically my final output will look like, I think if u managed to fix the classification then ok already

30 based on my dataset

I group my classes using the word. For example “good”, “morning”, “help”, “please” etc

So i have 30 classes

1 class 1 word

Please check the attached files. Let me know if you can fix it in 1.5 days.

Kĩ năng: Python, Machine Learning (ML)

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Về Bên Thuê:
( 0 nhận xét ) Puchong Batu Dua Belas, Malaysia

ID dự án: #29486523

1 freelancer đang chào giá trung bình $56 cho công việc này

asifmahfuz1405

hello sir, i am highly interested in your project. i have gone through your requirements and i believe i can be a valuable asset for your project. i am an expert in machine learning, deep learning and computer vision i Thêm

$56 USD trong 2 ngày
(8 Nhận xét)
3.8