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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11 views

Is there a ready-made webpage component classifier?

I'm trying to solve a problem where I need to classify what are the components of the webpage (button, text, list, container, etc...) based of a screenshot. Is there any ready solution for that?
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Training a YOLO-style object detector

tl;dr I'm trying to train a small CNN (two conv layers and two connected layers) to find humans in the COCO dataset. Is my network big enough, and if so, roughly how many epochs of training will it ...
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Yolov3 Tiny: What do each of the 2535 cells detect?

Source: https://towardsdatascience.com/yolo-v3-object-detection-53fb7d3bfe6b According to this image, it says the red grid is responsible for detecting the dog. Similarly, do other cells detect "...
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Is it advisable to use a model which is underfit but gives very high accuracy?

I am training a model for a single-label classification task in Vision. In this training, I am using oversampling of all the classes, and MixUp augmentation, along with rotation and dihedral ...
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Can landmark detection be only used for faces and human bodies?

I want to use landmark detection for finding specific points of interest in an indoor setting e.g. bedrooms, bathrooms etc. Is it possible to use it? So far I have only seen landmark detection being ...
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Less parameters - in general within ResNets

My question is about the parameters of the ResNet. Why does the network tend to have fewer parameters than the VGG? This would be the case if I got the paper and the summary from Yannic Kilcher ...
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Is it ok that my computer vision dataset just is loads of frames and images instead of video?

I am new computer vision and I am having a dataset with consecutive frames of videos. I want to ask that is it okay? How will you deal with it to output a video with some detections?
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Inputting Unnormalized Data into Pretrained Resnet

Quick rookie question, I was wondering, in theory, what would happen if I input unscaled and unstandardized byte image data into a pretrained Resnet (namely, from Pytorch's library). Would it still ...
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What should be the input shape for convLSTM if ResNet-50 is applied?

I have a dataset 12 videos. Each video is comprised of 179 frames. On these frames, I have applied ResNet-50 to extract features, and I received (179,7,7,2048) features. As far I know, 179=Total ...
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Applying GradCam to video classification models

In the original paper, it says that GradCam visualization can be applied to any convolution based model. The problem is stated for convolutions that process images. In my case, I am classifying videos ...
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Distance Agnostic classifier using deep learning techniques

This might be a challenging classification problem. In this classification, problem distance plays a major role. Here, the Category of the object would change if the distance factor varies. For ...
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Merging multiple classfiers

I am designing a classifier that takes as input features matrices of different dimensions, for example (Nx5, Nx10, Nx100, Nx1000) using visual bags of words of distinct dictionary sizes and methods (...
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Normalization vs standardization for image classification problem

For day and night image classification, is it better to normalize or standardize images? In general, when should I use each method? I am interested in with example why one method is preferred over ...
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crop part of image from image, change it and put it same place in original image

I have image (think of image of small plant) with bounding box. For data augmentation I want to rotate (45 degrees) the image (plant) in bounding box, and place it at same place in original image. so ...
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Correct dimensions of a Siamese network Input array

I have an image dataset where the folder structure is as follows- there are 900 folders (all of which will be classes) and in each folder, we have a varying number ...
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Unet Overfitting for binary segmentation of fake images

I am working on a project where I am trying to detect and localize forgeries in images. I am using the CASIA v2 dataset and using Unet model for the task. I have the binary masks of all the images in ...
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12 views

Training the network with some batch size - code

There is my "training" code below, I wrote it based on one youtube tutorial. I don't understand actually one part: batch_X = train_X[i:i+BATCH_SIZE], batch_y = train_y[i:i+BATCH_SIZE]. How ...
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Why YOLO algorithm predicts B boxes for each grid cell S?

In yolo each grid cell predicts multiple bounding boxes lets say in YOLOv1 it predicts B=2, what is the advantage as it only predicts class probabilities only once for each grid cell. If that so why ...
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One hot vector output in classification task

I'm working on CNN model and I used one hot vector type of labels. The number of classes is 3: [1,0,0], [0,1,0], [0,0,1]. net(x) I'm getting such an output: [0....
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Checking trained CNN on the images

I trained my CNN (model) classifier and want to check it on some new images. I have image x, so this syntax works for me for one image: torch.argmax(model(x)) What ...
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Using machine learning to find the most similar image that contains another image

As the title states I want to use ml (maybe some kind of CNN autoencoder?) to find the most similar image (I have a list of 10k+ images) within another image. I am currently just using opencv with ...
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CNN Color Invariance

For the task of detecting an object of any color, if we train our CNN only with images that only contain that object in one or two colors, will the accuracy of our model's predictions be affected for ...
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1answer
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Small object detection preprocessing

I am currently working on an object detection project in which I amtrying to detect very small objects 50x50 object in a 2k image. EfficientDet produced a very low result if I just put the raw ...
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How to annotate the object more efficiently

I want to perform object detection and object counting on the given below image using neural networks. My first step will be to annotate and label each object present in the training set of images. In ...
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Value of AP and AR are -1.000 in evaluation

As I understand, the AP amd AR calculation are as of follow: ...
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Testing trained model on the image from the test set

I trained my EfficientNet (CNN) and got accuracy=0.73. The question is how to check it on one concrete image from the testing set? How to write a code in python for it? I described the testing set ...
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23 views

What is better opensource alternative for identifying small face other than yolo?

I was trying to identify small face meaning that I want to know who that face belong to according to training dataset. I have previously use yolov4 to detect small object before and I know the ...
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Does PIFUHD 3D reconstruction model preserve sizes?

This is little conceptual question. I am working on 3D reconstruction using deep learning from 2D images. I came across PIFUHD model which is developed by Facebook and I have a question regarding that ...
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Train only Region Proposal Network in faster RCNN architecture

I am looking for a way to used my pretrained EfficientNetv2 model and turn it into an object detection. Is there anyway, I can put my pretrained model as a backbone and only train the region proposal ...
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Vgg16 model validation accuracy is stuck

I am working on a CNN model for MRI brain images classification (Alzheimer disease), I use transfer learning method for image classification - vgg16 model trained on ImageNet (1000 classes). I’ve ...
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35 views

CNN can't predict images outside the dataset

I am using celeba dataset to train my CNN face landmark detection model. Here is my model ...
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How can I use COCOAPI/PyCOCOTools to evaluate the performance of Tensorflow Lite models

I have used the Tensorflow Object Detection API to train models on a custom dataset. The tensorflow object detection API also allows evaluating the trained models on a test set and gives results in ...
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1answer
26 views

face landmark detection cnn loss not converging in tensorflow

I am trying to build face landmark detection model using simple regression.I used celeba dataset which has 5 points hence 10 output units.I used grayscale and normalized image as input. Here is my ...
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39 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
33 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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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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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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30 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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26 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
37 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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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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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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565 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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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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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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157 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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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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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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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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