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Questions tagged [image-recognition]

A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhancement (in particular, pattern recognition and projection).

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How to filter out babies from image dataset

I'm trying to perform a large image dataset clean up (filtering all the minors\babies from it). My initial approach was to utilize age detector, such as https://github.com/deepinsight/insightface/...
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How can I train a model for localizing objects(classification not required) in Python

I need to make a model that creates bounding box around objects(but does not classify them) for a competition. Which libraries or pre-trained models should I use. I need values of x1,x2(x1+w),y1,y2(y1+...
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Implementation of Siamese network

What would be the ideal ratio of positive, negative image pairs, and the number of image pairs to classify if two images are of same person in Siamese network ?
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3answers
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Where/How to start? [closed]

I want to create an application that recognises diseases from images, I know this require databases of images and image segmentation but where do I start? What should I start learning? I know nothing ...
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1answer
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Useful metrics to compare network-output image to true image?

I'm designing a supervised network that would require to output an image. I'm wondering what are the best metrics to find similarity between the output and actual target image. So far, my best ...
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Recognition of objects in almost plain background

I want to recognize climbing holds in a climbing wall. I thought about implementing my own heuristic algorithm for background detection because it's almost plain, but I was wondering if this kind of ...
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173 views

“10-year-challenge” data for age algorithms? [closed]

Both on FB and IG, I see people posting themselves before 10y and now. I have no idea how this challenge started. Could it be a way to collect a colossal amount of data, that could be used to train ...
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image caption generator

I see two models of image caption generator online: In the above model, the first LSTM cell of decoder takes the entire image as an input. In the above model, all the LSTM cells of the decoder take ...
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1answer
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Given a 12x12 binary image (only black and white pixels) what is its dimensionality? And how can I define dimensionality of a data space?

Suppose I have a grid 12x12 of pixels that can be only black or white. I can't understand if the dimensionality is 2 or 3. I mean... Is dimension given by 12x12 or 12x12x2 ?
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1answer
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What is a suitable Tensorflow model to classify images into foggy/not foggy?

I want to classify photos taken by multiple webcams that are operating in mountainous regions into foggy / not foggy. The photos are in various sizes and were taken under very different light ...
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1answer
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Sobel Operator || Pixel Constraint

I am trying out the Sobel vertical operator to identify vertical edges in a picture. In each image there is one rectangle but the difference is that in 1 image the 2 vertical lines in the rectangle is ...
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1answer
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Face embedding of unseen images

I've read about FaceNet but the main problem is still unclear for me. Does embedding work on the trained images only? Or once trained on a big dataset it will readily cluster unknown faces without re-...
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i got the following error : 'numpy.ndarray' object has no attribute 'detectMultiScale' to show image in python?

import cv2 videoCam = cv2.VideoCapture(0) face = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye = cv2.CascadeClassifier('haarcascade_eye.xml') nose = cv2.CascadeClassifier('...
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How can machine learning be used in invoice processsing

I have an invoice form (which may be either in pdf or jpg) from which I need to extract fields such as invoice number, date, name, address etc. These invoices have different templates and also be ...
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Studies about computer vision with highly similar images

I'm looking for studies, academic publications, papers, blog post, or anything that relates to use cases in which image recognition have been used with highly similar inputs. When using the word "...
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1answer
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Is it possible to train this image classifier?

I'm writing a mobile app that will enable a user to scan a Craft Beer Label from a bottle, tap, six pack, etc. The scan will only work for my customers who are the Brewers themselves, so I will have ...
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2answers
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How to transform a folder of images in a csv file

I have a folder with a lot of images that I want to use to bild a classificator using a SVM model in python with sklearn. I've always used csv file as train/test set with sklearn, how can I make it? (...
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2answers
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Counting non-overlapping objects in a semantic segmentation prediction mask

What is a good way to count the number of roofs detected by a CNN in the following output on the right (produced using keras/tensorflow): I need to count the discrete shaded areas and estimate their ...
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Generating labeled dataset for training a neural network

I am currently working on a project in which i'm supposed to classify whether an image contains a translucent watermark or not. This is hard to do with standard object classification or template ...
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2answers
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When using Data augmentation is it ok to validate only with the original images?

I'm working on a multi-classification deep learning algorithm and I was getting big over-fitting: My model is supposed to classify sunglasses on 17 different brands, but I only had around 400 images ...
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Rain radar image noise reduction and cleanup

An application that I am building is plotting rain radar images on map. The images are transparent PNGs that are sourced straight from the local meteorological service. As can be seen in the example, ...
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103 views

Using a custom R generator function with fit_generator (Keras, R)

I'd like to train a convolutional network to solve a multi-class, multi-label problem on image data. Due to the nature of the data, and for reasons I'll spare you, it would be best if I could use a ...
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1answer
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In handwritten digit recognition problem using logistic regression, what changes needed to add another class “Not a Digit”

In handwritten digit recognition problem using logistic regression, normal implementation would forcibly classify even a picture of dog or cat as a digit. To eliminate this, what changes are needed to ...
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1answer
47 views

Does image resizing lower the prediction accuracy of MLP?

I am implementing a vanilla neural network (MLP) to do image classification in python using tensorflow on images of honey bees to detect their health status. The images in my dataset are of different ...
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1answer
67 views

Why my model can't recognise my own hand written digit?

Currently i am working on digit recognizer[0-9]. My model train accuracy 100% and test accuracy ...
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1answer
55 views

image recognition: fully connected network vs CNN

To recognize handwritten digits, I have a fully connected network, containing only 2 layers: input layer (all pixels of the image) and output layer (0 or 1). I use the simplest linear regression for ...
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1answer
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Does CNN take care of zoom in images?

Suppose a convolution neural network is trained on small images of an object, say flower, as in following 3 training images: Will this CNN correctly classify if the same object is present in zoomed ...
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1answer
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How can we use machine learning to distnguish between similarly looking images

How can I build a model which can distinguish between Milk and Phenyl? I want to predict whether a given item is edible to eat or not. If I train a model with thousands of photos of Milk and Phenyl ...
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1answer
672 views

How to properly save and load an intermediate model in Keras?

I'm working with a model that involves 3 stages of 'nesting' of models in Keras. Conceptually the first is a transfer learning CNN model, for example MobileNetV2. (Model 1) This is then wrapped by a ...
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1answer
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What is difference between intersection over union (IoU) and intersection over bounding box (IoBB)?

Can someone give a detailed explanation IoU and IoBB along with that the differences between them.
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3answers
346 views

Unbalanced training data for different classes

What precautions do I need to take while trying to develop a CNN for classification of images if there is much more training data for one label. For example: ...
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Magnification factor in image classification

If a CNN is trained on images focusing on an object, will it also recognize when multiple such objects are present in the image? For example can a network trained on single flower images also ...
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1answer
91 views

Detecting abnormal 'cat' behaviour via Supervised Learning

A few work colleagues and I were looking through a recently replaced 'cat', we had in the workplace. For those of you which are curious, the 'cat' in this context, refers to a specific type of pump ...
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1answer
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What does the co-ordinate output in the yolo algorithm represent?

My question is similar to this topic. I was watching this lecture on bounding box prediction by Andrew Ng when I started thinking about output of yolo algorithm. Let's consider this example, We use ...
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Can we compile CoreML on Server?

I am working with CoreML and ARKit for Face recognition. But i don't want to build CoreML model with app. I have make a coreML model with python Turicate. I want this model to be put on server and it ...
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How to implement facial attendance system using less number of images of particulars

I have a project to implement facial Attendance where I have 5-6 images of particular and when individual comes, model should map the current image with person's earlier available images so if ...
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0answers
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How to understand log-likelihood for generative image model?

I'm reading a paper on generative image modelling. In the paper, the authors compare various approaches by listing their "negative log-likelihoods" (see screenshot). What does this metric translate to ...
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1answer
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How to check two images(one is original image and other one captured by mobile) similarity using deep learning?

My problem statement is - In my project, original image of product is stored in database. Now whenever any person uploading that product's camera pic(for internal audit process) then I need to verify ...
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Applying a Convolutional Neural Network to Large Scale Satellite Imagery

I'm applying a Convolutional Neural Network (CNN) for semantic segmentation to map out habitats from satellite imagery. More specifically I'm using Mask-RCNN (paper and code) to a large scale ...
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1answer
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System Requirements to train a Image Recognition Neural Network

I have 6000 Images to be trained on a Neural Network. My current PC Specs :- 32GB RAM, i5 2 core Processor, Standard GPU (No work going on GPU), 1TB Hard Disk My Neural Network Specs :- 3000 ...
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Cameras for automatic customer service machine [closed]

For my university project, I am planning to build an automated customer service machine. One which recognizes when someone approaches the camera according to says hello, etc. Also, I am planning to ...
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0answers
38 views

Better to crop or compress training data?

I've been trying to make an object recogniser in Tensorflow and have used labelImg to classify large electrical transmission towers at varying distances. In order to make 10-16MP (~2-7MB) images train ...
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612 views

Converting video into frames using openCV

I am converting video into video-frames using the given code converting video into frames ...
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1answer
98 views

Why is convolution filter used instead of correlation filter in CNN?

When I saw the two results of applying convolution filter and correlation filter, the results have the same distribution and are just flipped. Why is convolution filter used instead of correlation ...
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2answers
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Should we keep all channels when doing image classification?

I am discovering the world of image recognition and now trying to build an image classifier. The set of images I have have the shape (101,101,3) which means that it has 3 channels. If I'm not ...
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740 views

OSError: cannot identify image file <_io.BytesIO object at 0x7f5b2d2d9e60>

I created a lmdb dataset of images and labels but on reading the images, it is giving me error which I can't understand. Code: ...
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1answer
28 views

Is it possible to make tensorflow print out everything it see in a given image and not just the top five results?

I'm working through the python API tutorials for Tensorflow and I'm seeing the results that are normally displayed, but it's always giving me the top five results. I'm trying to discern all ...
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2answers
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What is the loss function defined by Mnih and Hinton in their paper “Learning to Label Aerial Images from Noisy Data”?

In section 3.3 of the paper, they state that they use the cross entropy. Then they define the probability for a label to be a false positive as $\theta_0$ and a false negative as $\theta_1$. They use ...
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Where can I find a dataset of images of faces and descriptions of them?

I'm doing an ML project that generates descriptions of pictures of faces. Is there a publicly-available dataset that has a set of face images along with a short description of what the face looks like?...
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Machine Learning & Image Recognition: How to start?

I've been a full stack web developer for 15 years now and would like to be involved in machine learning. There is already a specific scenario for this: We have a database with several million products ...