This is my input image I have this code to overlay the segmentation from input image with color # sample execution (requires torchvision) from PIL import Image from torchvision import transforms i...

I am using a Unet model for semantic segmentation - I have a custom dataset of images and their masks both in .png format. I have looked in the online forums and tried stuff, but not much works? An...

I have a single-channel image where each integer pixel value maps to a string. For example 5 -> 'person'. I'm trying to create an interactive image where hovering over a pixel will display it's cor...

The COCO dataset is very large for me to upload it to google colab. Is there any way I can directly download the dataset to google colab?

I have a binary mask for each image, with each mask pixel having value of either 0 or 255. Now because my image segmentation needs images of fixed size, I will have to resize the images and the mas...

I am working on Medical Image Segmentation. I have two classes. class 0 as background and class 1 as a lesion. As the dataset is highly unbalanced, I am using loss function as (1 - weighted Dice co...

How do you compute the top k accuracy in semantic segmentation? In classification, we might compute the topk accuracy as: correct = output.eq(gt.view(1, -1).expand_as(output))

I am trying to train a UNET model on the cityscapes dataset which has 20 'useful' semantic classes and a bunch of background classes that can be ignored (ex. sky, ego vehicle, mountains, street lig...

I first explain my task: I have nearly 3000 images from two different ropes. They contain rope 1, rope 2 and the background. My Labels/Masks are images, where for example the pixel value 0 represen...

From a segmentation mask, I am trying to retrieve what labels are being represented in the mask. This is the image I am running through a semantic segmentation model in AWS Sagemaker. Code for...

I have the results of semantic segmentation masks (values between 0-1, requiring otsu thresholding to determine what's positive) which I'd like to plot directly on the RGB image with different rand...

Given batched RGB images as input, shape=(batch_size, width, height, 3) And a multiclass target represented as one-hot, shape=(batch_size, width, height, n_classes) And a model (Unet, DeepLab) wi...

I'm experimenting with FCN(Fully Convolutional Network), and trying to reproduce the results reported in the original paper (Long et al. CVPR'15). In that paper the authors reported results on PAS...

There is a famous trick in u-net architecture to use custom weight maps to increase accuracy. Below are the details of it: Now, by asking here and at multiple other place, I get to know about 2 ap...

I just implemented the generalised dice loss (multi-class version of dice loss) in keras, as described in ref : (my targets are defined as: (batch_size, image_dim1, image_dim2, image_dim3, nb_of_c...

I am trying to do semantic segmentation with Keras and when trying to load the images i get this error using flow_from_directory method. Found 0 images belonging to 0 classes. Found 0 images belon...

I am trying to deploy a trained U-Net with TensorRT. The model was trained using Keras (with Tensorflow as backend). The code is very similar to this one: https://github.com/zhixuhao/unet/blob/mast...

I would like to customize deeplab for image segmentation using my own dataset ? Is this achievable by retraining ?

Context Suppose we have some 1D data (e.g. time series), where all series have fixed length l: # [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11] index example = [ 0, 1, 1, 0, 23, 22, 20, 14, 9, 2, 0, 0]...

Facing an issue in loading converted TFLite model into android application. Model: Deeplabv3 Mobilenetv2 (Trained on Pascal VOC) TFLite version: 1.10 Used tflite_convert for converting pb file in...

I am training a U-Net in keras by minimizing the dice_loss function that is popularly used for this problem: adapted from here and here def dsc(y_true, y_pred): smooth = 1. y_true_f = K.flatten(...

I'm trying to implement SegNet in Keras (tf backend) to do semantic segmentation. The most impressived trick of SgeNet is to pass max-pooling indices to the upsampling layers. However, there are m...

I don't quite understand the following: In the proposed FCN for Semantic Segmentation by Shelhamer et al, they propose a pixel-to-pixel prediction to construct masks/exact locations of objects in...

Does it make sense to combine cross-entropy loss and dice-score in a weighted fashion for a binary segmentation problem ? Optimizing the dice-score produces over segmented regions, while cross en...

I know the imbalance in an image classification problem such as the cat vs dog classification，if there are too many cat images and too few dog images. But I don't know how to adress an imbalance in...