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 do I achieve MAE < 8 using ResNet50 on this dataset?
I've been up all night trying to achieve MAE < 8 for this age recognition dataset: https://people.ee.ethz.ch/~timofter/publications/Agustsson-FG-2017.pdf
It is for an online class I am taking, the ...
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Counting Number of Holes in an Image of Cheese
I've been assigned a project that involves writing a script to detect the number of holes in an image of cheese. My background in AI is quite limited, so I was wondering if anyone could give me a good ...
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How can i create model to match nested geometric image with child geometric images
image1 is a nesting file and image2 is child file ,i want to find child file is contain in nesting file or not.We tried using random forest but it did not work.can you suggest some good image matching ...
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How to use additional features in image captioning?
I have the following question - is it possible to train a model based on Transformer architecture to use additional attributes to generate a caption for an image?
For example, I have a dataset with ...
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Text and Checkmarks Extraction from an Image
I am working on a project where in I have a filled form which is a safety inspection checklist and I am processing it through AWS Textract.
I am able to fetch text, layout, tables, signatures but ...
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Accuracy difference between 1-channel grayscale and 3-channel grayscale detection model
I have found no similar questions to this online, or answers for that matter.
I am using cameras that output a grayscale image, which I feed into a Yolov8 object detection model (Specifically yolov8m-...
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Can a location be derived from a compilation of paintings?
I have added a link to the collected paintings that were put into a video below.
I apologize for the quality, I had to gif and reduce it to fit here. (The SE team may consider increasing the size ...
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Flickr8k+PyTorch, CNN+LSTM predicts always same words during model testing
I'm a beginner in Machine Learning and I'm working with the Flickr8k dataset (it contains ~8000 images, every image has 5 captions: ~40000 pairs).
I splitted the dataset in training (70%) and ...
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Object Classification Dataset Creation
There is a problem I've faced recently which I'm not sure my approach is proper or not. There is bunch of field videos which I run a semi-supervised detection model to extract crops to train my ...
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Histogram of Oriented Gradients (HOG) - Why normalize 16x16 blocks and not the whole picture?
I'm trying to learn Histogram of Oriented Gradients (HOG)
I understand why we compute the gradient and the orientation and also map every gradient into a 9 binaries histogram that spans from 0 to 180.
...
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Seeking Solutions for Generating Text Descriptions from Diagrams, Infographics, Charts, etc
I am currently on a quest to find an efficient way to generate meaningful text descriptions (or alt text) from visual representations such as diagrams, infographics, charts, plots and the like. ...
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What (ML) algorithms take an image as input and optimal action as output?
I have a given 2d image describing a top down view of a grid (think e.g. a labirynth.)
I want an algorithm to take it as an input and return a single action to be performed in the setting of this grid....
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Training a Face Recognition model using benchmark datasets
Is it recommend (or conventional) to train, for instance a face recognition method, using benchmark datasets such as XQLFW, RFW, CALFW, etc.? I would like to fine tune my model so it is more robust to ...
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Why facenet works better than siamese network
I have been reading about face recognition literature. I stumbled upon siamese networks with contrastive loss and the facenet paper. Both approaches use metric learning. The difference is mainly in ...
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Is there any way to aquire image and video URLs from a large amount of facebook ads for research?
I have aquired a lot of URLs to some political ads from the Meta ad library API. As far as i can tell, there is no way to automate the aquisation of the image and video URLs from these ads. Is this ...
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Avoid decrease in accuracy with depthwise convolution
I have been optimizing the model for resource-constrained IoT device, and for this, one of the automated choice was to depthwise separable convolution. However, withit, though the number of flobs, ...
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How to differentiate Bitmojis gender?
I have seen this Project Larry-zx's Githubproject
It is used to create a .pth file which can differenciate between a bitmojis gender.
Now I have created that .pth file but no idea how to use it, ...
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pytesseract performance for digit recognition
The sequence in the following image
is correctly recognized by pytesseract via the usual function "pytesseract.image_to_string". But the following image with a similar sequence is not ...
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How to train AI to recognize a Snapchat's bitmoji's gender
I would like to enable my Python script to get a vague idea of a bitmoji's gender.
I found these two git repositories that are able to differentiate between them.
How would I use them to have my ...
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Applyingv a 2D mask onto a 3D rgb color list
Problem
I have the following image data as a 3D numpy array containing rgb values of the image in a (n,n,3) shaped list (Image). I also have data of the corresponding black and white mask image in a (...
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Using CNN to extract channel network from old maps
I am a numerical modeller working on a flow problem. I have developed a channel network simulator to model fluid flow through an irrigation network.
As part of my inputs I have to use old maps (as old ...
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CNN model with images - 100% accuracy on validation and test sets with limited data?
I have a binary classification problem (e.g. if there is a human in the room or not) with a small dataset of images from a thermal camera.
Originally, those were 7 videos, which I have converted into ...
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Object Detection without annotations and labels
Problem Statement:
I am given 2 sets of images. All the images in both sets are without annotations and labels.
First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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Floor plan analysis
Given an image of a floor plan, is there a known algorithm I can use to understand measurements of all apartments present ? (for example, that means in the attached picture understanding there are 4 ...
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Can you use a Confusion Matrix for a image detection problem?
I have read the classic examples of using a Confusion Matrix for a classification problem. ("Does a patient have cancer, or not?)
The ML system I am working with is for detecting objects in an ...
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Determine postion of dart in dartboard
I'm new to machine learning and I want to built my first project.
I decided to write an application which determines the postion of a dart in a dartboard.
The neural network would have the following ...
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Algorithms to do a CTRL+F (find object) on an image
We all know the CTRL+F "Find text..." feature in text editors / browsers.
I'd like to study the available algorithms to do something similar on an image.
Example of UI/UX: let's say you have ...
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How can I correctly identify an item within a larger image, but also detect if the item is the correct orientation?
I have some machinery at work with a small sticker I am trying to detect within a larger image. I am familiar with object detection techniques based on a trained classification model, but to further ...
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Is there any difference between classifying images by their type and by the objects they represent?
Let us suppose that I would like to train a machine learning model for classifying images according to their types (for example, photographs and drawings).
The techniques that I can use for this would ...
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Trouble with anomaly/novelty detection (on microscale) - need easy practical guide with Keras
I am relatively new to the field of machine learning. However, I already have solved simple image classification tasks with Keras (for example building CNNs and classifying MNIST...). The rough deep ...
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Reducing Validation loss for Triplet Loss Embeddings
I'm trying to create a facial recognition detector using triplet loss followed by a kNN algorithm.
I have roughly 10000 input images with 3 different classes, input size is 80x80. Model structure uses ...
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How to improve the accuracy of the test set of LRCN-based video classification model
An existing LRCN-based video classification model consists of resnet152 provided by torchvision and an LSTM layer, and this model achieves 92% accuracy on the UCF-101 test set.
The input range of this ...
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Classifying visual environment in Tensorflow CNN (video analytics)
I am given a selection of videos of users exploring simulated 3D enviroments (kind of looks like the Sims video game) and I am tasked with being able to classify each room using a tensorflow framework....
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CNN application assessment
I would be glad if someone could give me some hints and assessment for the following project. (I'm relatively new to ML and DL and having only a little theoretical knowledge)
My goal is to build a ...
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Predict saved model from live camera for multiclass recognition
I have developed a model with relative good accuracy. I am trying to predict new input image from live camera by detecting or set a bounding box where only hand region are capture. I used the code ...
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Classification report and confusion matrix problem
I am working on sign language recognition system using HOG and KNN. I have 26 classes of 180 images per class. The dataset was split into 1/3(67%) for tanning and 2/3(33%) testing after feature ...
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Dummy vectors and performance measurement for vector search Face Recognition
I have about thousands of person face (from celebrity dataset LFW), which each person represented by 512 x 1 vector. I stored it on vector DB to build face searching system using embedded feature (...
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What is the impact of changing image sources on an image recognition?
I have a fairly general question pertaining to an image recognition ML model. I’ve recently developed an image recognition model using a single camera collecting more than 5000 images and then trained/...
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Siamese Neural Network for massive class variation
I have case to check whether the person has been registered into a database,and if the images has high similiarity with one of the image in the db, i want to retrieve the image information (name, id, ...
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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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Basic doubt regarding "training" of a YOLO model
So I have just recently started exploring machine learning, and for a project I was required to train the YOLO v5 model. I first tried it on the coco128 dataset:https://www.kaggle.com/ultralytics/...
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Count repeating "objects" in a picture
This is my first data-science project and I would love to get some guidance to know how to get started.
My problem is the following:
I want to count objects that are in a picture. This picture has a ...
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CNN regression. help to improve current model [closed]
I have time series grey scale images that show movement of fluid with different densities.
I want to predict a pixel value for time t, with (t-3),(t-2),(t-1) 2D images as inputs.
I am figuring out how ...
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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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Split npz Dataset into Train/Test using Sklearn [closed]
I have a dataset of faces stored in an NPZ file that I would like to train it on Siamese Network. To do that, the dataset must be split into train / test using Sklearn. However, when I run the code to ...
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What kind of approach should I apply for face validation with using deep learning? [closed]
My research task is face recognition in cars with using deep learning method. Actually, in example we set an driver randomly and then the question is: Is this person driver or not?
So i created an ...
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Finding the position of an arbitrary object in a static image?
One common object detection scenario involves finding trained models in an arbitrary scene. For example, we can train a model to understand what a "bicycle" looks like, by providing various ...
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ResourceExhaustedError when building Sequential model
i have a big problem when trying to build my model,
...
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predict multiple letters in pixels matrix
I have a multilayer perceptron model that is trained to recognize handwritten English letters from an image. In the training set each image matrix had 784 pixel values. The labels of these images ...
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How to manage memory constraint and increase speed for 1 vs rest image similarity comparison for over 100k images for computer vision?
I'm looking for ideas on how to do things in a better way, efficiently when using Machine/Deep Learning.
I am working on a search improvement problem using Computer vision where I am thinking about ...
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