Mastering Background Removal: U2 Net Unleashed! | TensorFlow Image Matting Tutorial | U2Net

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In this tutorial, we'll walk you through using the powerful U2 Net architecture for image matting in TensorFlow, using the Python programming language. This cutting-edge project enables you to achieve high-quality background removal from human portraits with ease, giving your images a polished and professional finish.

Perfect for developers seeking to master the art of high-quality background removal, this tutorial equips you with the knowledge and skills to effortlessly remove backgrounds from human portraits. Elevate your projects to new heights with this cutting-edge technology. Join us on this coding journey today!

Timeline:
00:00 - Introduction
00:16 - What is U2 Net
01:23 - What is Image Matting
03:21 - P3M-10k Dataset
06:48 - U2 Net Implementation
09:20 - Training the U2 Net
27:41 - Testing the trained U2 Net
47:08 - How to improve it further
48:01 - Ending (SUBSCRIBE)

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Thanks. Hope have many videos from you.

nghethuatsong
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I have tried traing your model but for me the val loss keeps getting worse for every epoch I have tried data augmentation and regularization too but still facing the same problem

goodwill
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Hi,
I have trained my custom u2-net model by your video.
But there's an error i met is that missing the path of model.h5.
Could you tell me how to get the file 'model.h5' or how to solve it?
thanks

kghihvv
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Hi, A thorough explanation. Could you test the standard Unet model with a 3D dataset?

vijayalakshminiranjan
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hi, im getting this error "FileNotFoundError: [Errno 2] Unable to open file (unable to open file: name = 'files\model.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)". What should i do?

tpizyxw
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Is there any data set for a set of object types instead of only human portrait.. like a hairy puppy as an object.????

Magicmobi
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Hi,
Does the final resize decrease a quality of a images or not?

drmwnnrafi
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Can you make image extraction tools? I will pay for that

ravikatre