GitHub – aadityavikram/Background-Removal: Background removal of an image using OpenCV and Deep Learning.

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GitHub – aadityavikram/Background-Removal: Background removal of an image using OpenCV and Deep Learning.

Background-Removing

Background removing of a picture utilizing OpenCV and Deep Studying.

You are watching: background remove deep learning github

Setup :-

Python – > Python 3.6.5

OS -> Home windows 10 (OS build->17763.253) (Model->1809)

GPU -> Nvidia Geforce GTX 1060 (6gb)

CPU -> Intel Core i7-8750 @ 2.20GHz

RAM -> 16gb

Background of pictures containing an individual may be eliminated by operating photoshopservices.web

python photoshopservices.web

specify path of file when it outputs “Enter path of file: ”

runs on Keras 2.0.9

makes use of 100 layer Tiramisu neural community which was primarily based on the DensNet.

Refer: How to Remove Image Background Online for Free[2021] | Photoshop Services

the pre-trained mannequin shouldn’t be so correct and works finest when a single particular person is current within the image.

and as it’s 100-layer Tiramisu mannequin, re-training it will take days on my system.

pre-trained fashions may be downloaded at:-

*each fashions gave totally different outcomes relying on the picture*

Background of pictures not containing an individual may be eliminated by operating photoshopservices.web

python photoshopservices.web

specify path of file when it outputs “Enter path of file: ”

makes use of OpenCV

*photoshopservices.web gave higher outcome when deep studying was used with 2nd mannequin than when 1st mannequin or OpenCV had been used*

Course of for photoshopservices.web :-

1) Loaded the pre-trained mannequin.

2) Resized the picture to 224×224 because the mannequin was taking enter in the identical decision as seen from photoshopservices.web file.

GitHub - aadityavikram/Background-Removal: Background removal of an image using OpenCV and Deep Learning.

3) Eliminated the transparency channel earlier than getting predictions and resize the prediction to its unique top and width.

4) Pixel values above the edge issue had been transformed again to 255 and under threshold had been transformed again to 0 to exclude out of vary pixels.

Refer: Ada Fitur Baru Nih di Canva [Remove Background] – Iltekkomputer

5) Added again the transparency channel and transformed the array again to picture.

6) Saved the picture in png format.

Course of for photoshopservices.web :-

1) Grayed the picture and utilized canny edge detection, erosion and dilation.

2) Discovered the contours and crammed all of the contours.

3) Blurred the masks after smoothing it to make the contours clean.

4) Transformed the masks into 3-channel and blended it with foreground.

5) Added transparency channel to the picture to make background clear.

6) Saved the picture in png format.

Distinction and brightness may be elevated for higher background removing utilizing photoshopservices.web file

python photoshopservices.web

Put the dataset folder containing the coaching pictures in the identical listing as this python file.

Last pictures might be saved in the identical format because the dataset folder in a brand new skilled listing

Hyperlinks referenced :-

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