Questions tagged [computer-vision]

Computer Vision is a subfield of computer science which deals with analyzing and understanding images. This includes detection of objects like faces in images or segmenting images.

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25 views

Correct way of computing dice score for image segmentation?

In binary image segmentation, for given a set of images, it's true mask and predicted mask. How do you compute dice score? Should I compute the dice score for each image separately and then find mean ...
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1answer
24 views

best similarity measure for images with different angles

I want to compare different images (where the images are of the same setup but the angles with which the images are taken are different). I want to obtain some sort of similarity score. I tried using ...
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17 views

How metric learning works for content based item retrieval

I was doing some computer vision experiments and recently I have started learning about metric learning and the image retrieval problem. I was experimenting with the inshop image retrieval dataset to ...
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8 views

What is sub-pixel convolutional layer in ESPCN? [closed]

I am reading the ESPCN paper for single image super resolution. I am having trouble understanding the sub-pixel convolution layer mentioned. It would be wonderful if someone can provide a simple ...
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15 views

Labelling Images - Image Recognition

I'm new to image recognition and I've been tasked with implementing a YOLO classifier. Images I have relate to the installation of a product. So to train this custom dataset, I've been labelling the ...
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7 views

What is the difference between a bounding box and ROI (Region of Interest)

I was reading about the Fast RCNN for object detection. From what I understand, it uses pre-computed ROI's (using selective search) and uses these to predict the bounding box offsets and uses smooth ...
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1answer
28 views

How to model the probability of detecting an image, given it is seen multiple times

Are there any existing methods/models describing the probability of an object being detected by a computer vision algorithm given it is seen $n$ times at similar angles and orientations? I know that ...
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15 views

How to evaluate pix2pix?

As far as I know, to evaluate synthesized images it is proposed to use: human scoring, "Inception score", where in the second case the quality is rated based on a pre-trained Inception ...
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1answer
26 views

How to interpret fast-rcnn metrics?

I'm following this tutorial to fine tune Faster RCNN model, during training process a lot of statistics are produced however I don't know how to interpret them. what are major characteristics to look ...
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Faster RCNN is not able to recognize composed elements

I tried to fine tune Faster RCNN to realize object detection task with bounding boxes where I shall recognize face, eyes and mouth on image. However Faster RCNN seems to fail to recognize objects when ...
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1answer
17 views

What is the upscaling factor in super resolution with deep learning? [closed]

I have been reading papers on single image super resolution (SISR) and I frequently encounter X3 upscaling factor, X4 upscaling factors. Example: SRGAN mentioning x4 upscaling factor It would be ...
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22 views

How to convert RGB to One Hot encoding of Pixel in Pascal VOC Dataset?

I am trying to implement Semantic Segmentation on PASCAL VOC 2007 Dataset using Fully Convolutional Network. My Network outputs images of (Height, Width, Classes); but the training label masks are of ...
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1answer
87 views

Class token in ViT and BERT

I'm trying to understand the architecture of the ViT Paper, and noticed they use a CLASS token like in BERT. To the best of my understanding this token is used to gather knowledge of the entire class, ...
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1answer
40 views

How to estimate real distance between two detected objects in an image?

You may think this is a duplicate, but my situation is different than previously asked questions. The only information I have is the width and height of the bounding boxes of detected people. The ...
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18 views

How Does EAST detector implementation with VGG16 look? How many outputs does it have?

I was reading the Efficient and Accurate Scene Text Detector paper and saw the author reference VGG-16 as a possible stem "feature extractor" network. In the paper they say: In our ...
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1answer
155 views

Can somebody explain me the meaning of this sentence? (Color Similarity - Selective Search Algorithm)

This is a sentence from this article : Color similarity: Computing a 25-bin histogram for each channel of an image, concatenating them together, and obtaining a final descriptor that is 25×3=75-d. ...
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17 views

Predictions receiving in Unknown (8)[e,e,e,e,e,e,e,e] format from TensorflowJS Mobilenet

I have trained a mobilenet on diamond images to count diamonds in broswer. I then converted the SavedModel format to TFJS format. I have the following code in my JS file. ...
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6 views

Retrieving image masks from PASCAL and COCO segmentation annotations

How do I retrieve image masks for instance segmentation data which has annotations saved in the COCO and PASCAL annotation formats with python? The format is very confusing for instance segmentation ...
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29 views

Unable to Predict the custom trained mobilenet in browser using TensorflowJS

I am new to TensorflowJS and Javascript. I trained a mobilenet with images of diamonds using Tensorflow Object Detection so that it can detect Diamonds. The model is saved in SavedModel format. I ...
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1answer
26 views

Feature extraction from sequence of images with Siamese Neural Network

I am trying to train a neural network to recognize certain actions in short movies. Each such movie consists of a fixed number of frames, each frame - the image is of course the same size, after ...
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1answer
23 views

Training CNN: Understanding number data generated while training the model

I am training CNN on kaggle and my training and test datasets shapes are as follows: ...
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21 views

What is the difference in computational cost at inference time between object detection and semantic segmentation?

I am aware that YOLO (v1-5) is a real-time object detection model with moderately good overall prediction performance. I know that UNet and variants are efficient semantic segmentation models that are ...
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1answer
37 views

Transfer Learning on Resnets/VGGs — Validation accuracy can never be over 75%

I am trying to classify skin cancer images into two categories -- malignant and benign. Literatures suggest that using pre-trained resnet/vgg network achieves more than 90% accuracy. However, with my ...
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12 views

Machine learning model (neural network or SVM) for unequal feature matrices size

I have feature matrices obtained from visual bags of words model for various dictionary sizes. Example, Nx5, Nx10, …., Nx15000. Where N is the number of samples and 5, 10, …15000 are the visual ...
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17 views

Why are axes-aligned bounding boxes used in object detection

I understand (I think) why in object detection, the result is a rectangle: it is a simple shape that can be defined by 4 variables (2 pairs coords of opposite corners or 1 pair of coords + width and ...
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1answer
15 views

Which F1-score is used for the semantic segmentation tasks?

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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86 views

Yolo issue with detecting positives

I've recently tried to implement a Yolo detector for traffic light detection based on yolo v1 implementation in Tensorflow/Keras. My model really struggles with detecting small objects. Loss function ...
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5 views

How do you compare outputs from different augmentations for consistency training?

I'm trying to figure out how papers using consistency train on unsupervised data, and I'm stuck on how outputs from different augmentations are compared. Since the augmentations are transformations, I ...
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100 views

How to convert VGG VIA Instance segmentation annotation to COCO/PASCAL for Tensorflow Object Detection?

I have VGG VIA JSON annotations for instance segmentation for counting diamonds from a given image. The annotations are mixture of Circle, Polygons, Polylines. However, I am planning to use the ...
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1answer
38 views

LED status detector [closed]

I have a piece of custom device that displays its working status by blinking LEDs fitted on the device. for example, the led is ON means the board is on led is OFF means the board is off. red led ...
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16 views

Refactoring Tensorflow 2 to Distributed Tensorflow for CNN

I have been trying to reproduced this paper that is training a CNN with Tensorflow. Unfortunately, I only have access to limited computing resources. I have a few raspberry pi that I was thinking of ...
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7 views

How to predict multiple set of coordinates for signboards text localisation through neural network

I am creating a signboard translation model from scratch. I have images of signboards where there are multiple texts and I have the corresponding set of coordinates for multiple texts. I want to ...
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1answer
48 views

What I need to write in the line level of torch.vison for 21 classes?

In this code I found , line labels = torch.ones((records.shape[0],), dtype=torch.int64) ,that there is only one class and 0 in the case of Faster RCNN is reserved for the Background. What would be ...
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1answer
49 views

How can I save my learning rate on each finished epoch using Callbacks?

I used LearningRateScheduler for my model training. I want to save learning rates on each epoch in CSV file (or other document files). Is there any way to save those learning rates using callbacks?
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14 views

Liveness Detection System - Suggestions

I am trying to build a liveness detection system but till now I haven't been able to generate any significant results. I read the article by pyimagesearch this on the same topic but no luck. Tried ...
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1answer
52 views

How to plot multiple models val and traing acc/loss curve from csv files?

I trained multiple CNN models, after that, I saved models details (Like , training/Validation Acc/Loss ) by callbacks by using this codes : ...
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13 views

Saving the Autoencoder predicted image to a new directory

I trained an autoencoder model in Keras to generate denoised images given noisy images. The predicted images are stored in the "result" directory, with the individual filenames appended with ...
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12 views

Denoising Prior to Image Classification

From what I have read, Denoising during preprocessing for image classification tasks seems to be a bit controversial. While on one hand it might improve classification accuracy, the computational ...
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26 views

Mask RCNN 1 class only

I am looking to use only one class, person (along with BG, background), for the Mask RCNN object detection. I am using this link: https://github.com/matterport/Mask_RCNN to run the mask rcnn. Is ...
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12 views

Comparison of different ways of Upsampling in detection models

There are various ways to increase the resolution of tensor in (width, height) dimensions, frequently used in detection models like ...
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6 views

What should be the MINIMUM value of 'k' in LSH (Locality Sensitive Hashing) for 20M + data points?

For 20M + images, I'm thinking about using LSH for similarity of Vectors or data points or more precisely image Embeddings ...
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15 views

Unidentified Image error while loading images on Google Colab

I'm writing a code to make movie genre classification with movie posters. I opened a github repository where I put all the posters and cloned it on Colab. Until here, eveything works fine. When I'm ...
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26 views

Energy-Based modelling vs Deep Learning

I am doing some research on machine learning algorithms in the context of a seminar, which focuses on Energy-Based Modeling vs Deep Learning Modeling specifically in working with images. Now I know ...
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21 views

Darknet and Data Augmentation

In the darknet deep learning framework .cfg files we see parameters like angle, saturation, exposure These parameters are used ...
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17 views

Object detection in RGB-D images

Can you please recommend papers/github or smth about object detection on RGB-D images (NOT 3d cloud points).The result should still be objects in rectangles in the 2d image, as in the usual methods ...
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19 views

Statistical method to find the value which preserves the most information inside “most” of data points. (resize images to a common height)

So I have this data of around 88K images and I found out some interesting properties for my images. ...
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2answers
41 views

What is the best approach for detecting the defect?

Assuming that we have 10 same objects, they are lined up and equidistant. If any of them is rotated a very small angle(5 - 10deg), what is best method to detect them? I am using a camera to capture ...
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10 views

Evaluating the performance of tracking multiple objects detected with object detection

I have a ground truth dataset where the objects have been manually annotated and each object have been provided an ID that is consistent through time. There are no false positives or false negatives ...
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11 views

which image filter to use here

I have an image which is generated from noise using deep learning. When I zoom in on the image it looks like the image provided below. As you can see image is not sharp enough. I want to sharpen the ...
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9 views

Differential Learning Rates To Train Parts of A Network Faster

So I've had a rather "out there" idea. I want to train a dense network on a regression problem based on tabular data but I'd also like it to incorporate image data. My idea was to use a CNN ...

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