Multiclass Segmentation using UNET in TensorFlow | Crowd Instance-level Human Parsing (CHIP) Dataset

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In this video, we will learn about multiclass segmentation using the UNET architecture in the TensorFlow framework. Here, we will use the Crowd Instance-level Human Parsing Dataset (CHIP) which contains 20 classes.

Timeline:
0:00:00 - Introduction
0:00:30 - Dataset: Crowd Instance-level Human Parsing Dataset (CHIP)
0:05:51 - UNET Implementation
0:22:04 - Training the UNET
1:03:57 - Testing: Prediction and Evaluation
1:39:00 - Ending: SUBSCRIBE!!!

Dataset Name: Crowd Instance-level Human Parsing Dataset (CHIP)

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You are an amazing teacher. This tutorials helped me a lot and I learned many things. Thank you a lot sir.

junaidhassan

Amazing amazing video!!
Compact and general code and you included some extra features, like having 20 classes, your visualization, colormaps and performance evaluation and logging
Very useful video

husammasalkhi

Your hard work is really appreciable. You are doing an amazing job. Thank you for making such wonderful videos.🙏

vimalshrivastava

You are the best!!!! This explains a lot!!!

abellilo

Thank you very much sir, your the best. Please can you do a video on how to detect micro-organism in the image dataset of any human disease. Thanks

nkechiesomonu

When I provide colourmap as a array, COLORMAP = [[0, 0, 0], [109, 50, 255], [255, 50, 225], [196, 50, 255], [50, 80, 255], [50, 167, 255]],Its not working, Why is that?, I were got prediction only black colour image.

DimalChathuranga-ofet

I am trying to train a model for imbalanced class image segmentation task. I adopt the categorical cross-entropy loss as the loss function and "accuracy" as the metrics. It shows a very high accuracy in both the valset and trainset during the training, but when I explore the predictions, all the predictions are the background even when I use trainset and valset in the testing stage. May you give me some advice? Thank you.

Guiltyass

Kindly tell me how to get RGB code for different types of masks. like THERE ARE only 4 classes in my project(nucleus, background, fatcells and cell) . but I am getting 59 unique values for the RGB mask i have. how to handle this and get colormap file for such things

gousiakhanam

i dont have colormap for my dataset, what am i supposed to do?

joelsharonr

Do you have any repository that is implemented by custom training loop using Tensorflow, not by model.fit() method?

wonchulkim

How to create masks for multiclass semantic segmentation

purvi

Can i use my own data? And if i can how can i annotate the data?

zubairsk

how to generate .mat file for my colormap ?

nabiladnan

Hai sir! Really love your video which i learn a lot from your video. The things is, i be able to train unet, but i try to implement to deeplabv3+ model, but a lot of error are coming. I would love if you can help me in training multi class segmentation using deeplabv3+, because i already watch the model creation video of you deeplabv3+, just i want to know how to train it, im using the same way to train unet but it doesnt work. Thank you sir!

ipangraphy

So, why didn't you use iou as your metric like the one you used in the Skin Lesion Segmentation

KarimAkmal-xsex

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