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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A good way to use facial landmarks as input

We are planning to use facial landmark information as input to the model. Since there are more than 60 points, it doesn't look good to use 60 channels as inputs after one-hot encoding. I found a few ...
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Normalizing validation set in DL Model [closed]

I created a DL model for image segmentation. I normalized my training and test set by dividing them by 255.0. I then run predictions in new images (validation Set). However, I forgot to normalize them ...
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Create a model that can extract only specific data out of receipts or invoices?

I'm trying to build a model that is capable of identifying only some of the information on receipts and invoices. All the documents having different structure in image format. Sample Data : Click here ...
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1answer
32 views

Machine learning algorithms for identification and classification of Microorganisms

https://www.google.com/search?q=Viruses+images&tbm=isch&ved=2ahUKEwiB9-fsoL3sAhUJyHMBHWRZB-sQ2-cCegQIABAC&oq=Viruses+images&gs_lcp=...
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Detectron2 Alteranatives

Detectron2 is really good and it supports large number of models / but not all. Eg. Yolo. Do we have alternative to detectron2 which provide easy to use API for both model inference and retraining? ...
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Training CNN for object detection

I have an idea for build object detection model and I would like to share it with community in order to see if it makes sense. Dataset: I've gathered images with different shapes and annotated them ...
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2answers
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Troubles Training a Faster R-CNN RPN using a Resnet 101 backbone in Pytorch

Training Problems for a RPN I am trying to train a network for region proposals as in the anchor box-concept from Faster R-CNN on the Pascal VOC 2012 training data. I am using a pretrained Resnet 101 ...
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23 views

Normalization of CT scans

I trained an infection segmentation models on a large dataset of CT scans, and want to extend it to other datasets to show the ability of the model to generalize. What I found though, is that CT scans ...
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15 views

Train a cascaded network with a classifier in between

I am attempting to do a two-fold task. The input is an image and based on the input I want to pick another image from a set of images (classification task) and then use both the images to obtain an ...
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13 views

CNN Image resolution vs size/shape

a common technique to get an image to a particular size is by either resizing it completely which can lead to losing the aspect ratio or e.g. resizing the bigger side and then 0-padding the other. My ...
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how to calculate mean average precision of custom object detection algorithms in python

I know that for calculating mean average precision first we must have ground truth files for each image in dataset. I am following this tutorial to detect whether a person has mask on its image or not....
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What is the meaning of Face Recognition in wild and in static?

What is meant by when someone says face recognition on wild dataset and on static dataset?
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Machine learning algorithms for interpreting Companies brand/s logo/s

https://www.google.com/search?q=Company+brand+logos&client=ms-android-lava&prmd=isnv&sxsrf=ALeKk0218I-1fMd-hNXX_fAF8_fu6EOotA:1600348128111&source=lnms&tbm=isch&sa=X&ved=...
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EfficientNet function composition or Hadamard

In the page 3 of the paper of EfficientNet, there is a equation $$\mathcal{N} = \bigodot_{i=1...s} \mathcal{F}_{i}^{L_i} \big(X_{\langle H_i, W_i, C_i \rangle}\big)$$ where $\mathcal{N}$ is the conv ...
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1answer
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Machine learning algorithms and Computer Vision technologies for detecting 52 playing cards deck

https://en.wikipedia.org/wiki/Standard_52-card_deck https://en.wikipedia.org/wiki/Playing_card https://www.google.com/search?q=playing+cards&client=ms-android-lava&prmd=sinv&sxsrf=...
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CNN: How do I handle Blurred images in the dataset?

I have 30% blurred images in each classes. I have a total of 10 classes. I'm not allowed to drop these blurred images. How do I train the model to get better accuracy for both blurred and nonblurred ...
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1answer
41 views

Object detection is not improving although loss is decreasing

I am working on a project for detecting buildings from satellite images (using OpenStreetMap data as labels) using the Tensorflow Object Detection API. I recently upgraded to Tensorflow 2 and chose ...
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What is an impulse signal?

I am a newbie in computer vision. While other concepts seems to be well understood this far, I don't understand the concept of impulse signal and why they matter in computer vision? What are the use ...
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Detecting Deformable Curve in a Video

Problem This is a question my friend in mechanical engineering asked me. However, I am not an expert in computer vision/image processing, so I come here to seek help. Data The following are two frames ...
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2answers
32 views

Stamps detection using AI, Computer vision & Machine Learning technologies

https://en.wikipedia.org/wiki/Postage_stamp https://www.google.com/search?q=stamps&client=ms-android-lava&prmd=isnv&sxsrf=ALeKk02Ik_sWwymBctdONPasm7w0YNXcZA:1599240889888&source=lnms&...
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Differentiate twins, triplets images in Computer vision field

https://en.wikipedia.org/wiki/Computer_vision https://en.wikipedia.org/wiki/Twin https://en.wikipedia.org/wiki/List_of_triplets Will there be challenges in Computer vision field to differentiate ...
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Best object detection model where inference speed is not a factor?

As in the question I’m wondering what is the current best model for object detection in images where inference time doesn’t matter? Thank you in advance.
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Most accurate object detector for photos? Speed of detection not an issue

I just wanted people’s opinions on a particular problem I am solving. The images I have are photos not video and I need to classify the number of a particular object in these photos. If the speed of ...
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What is the difference between “Document Layout Analysis” / “Document Understanding” / “Document Structure Analysis”

All three terms sound super similar: [...] document layout analysis is the process of identifying and categorizing the regions of interest in the scanned image of a text document. A reading system ...
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263 views

Reducing the size of a dataset

I am trying to classify gestures. I am using Python's scikit learn library classification algorithms for that. I have collected depth images for this purpose. 200 samples are collected for each ...
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1answer
31 views

How to deploy a deep learning model in Flask (Python)? [closed]

I am still an amateur with respect to deploying deep learning models as a flask app. I want to deploy a VQA model based on MMF (Pythia) in a flask app. Github repository for reference. Can someone ...
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287 views

InvalidArgumentError: logits and labels must be broadcastable: logits_size=[32,2] labels_size=[32,200]

I am training a Reset model on Tiny-Imagenet dataset. When I am training the same model on Cifar-10 or Cifar100 I am not facing any errors. However, when I am using Tiny -Imagenet along with ...
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Best approach to deploy computer vision machine learning model as RestAPI and deploy in Azure

I have machine learning model which identify 2-wheeler and 4-wheeler vehicle by seeing videos of live camera which installed in parking area. ...
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How to generate custom image dataset for object-detection?

I have to build a custom logo detector from e-commerce images. I am aware of object detection techniques like YOLO, SSD etc and could find many resources on how to annotate a custom object detection ...
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173 views

Which is the “BEST” deep learning model for “Custom” object detection for images & real time. YOLO v3, v4, v5, EfficientDet?

Whenever I look for object detection model, I find YOLO v3 most of the times and that might be due to the fact that it is the last version created by original ...
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1answer
23 views

Bidirectional vs. Traditional LSTM [closed]

I'm working on image captioning problem, where I need to have an encoder for image and decoder for caption generation. Regarding the decoder, I've found a reference that uses Pytorch LSTM where ...
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22 views

reason why there is two dense layer?

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1answer
76 views

How to interpret skimage orientation to straighten images?

I have a bunch of images that I am trying to straighten so the images are horizontal (major axis is horizontal) but I don't understand the orientation output from ...
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1answer
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Which colour channel from a TIFF image do I have to use?

I'm going to use the following dataset to do semantic segmentation with U-Net network. LGG Segmentation Dataset This dataset contains brain MR images together with manual FLAIR abnormality ...
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10 views

Generate 3D models from screenshots or screen recordings

I was wondering if there existed any software or libraries that could turn a series of screenshots or screen recordings (such as livestreams or videos) of simple geometries into models that I could ...
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38 views

Image segmentation network to extract questions from an image of a test paper?

This is the sample document -> I want to extract questions along with the options. There are other question papers as which have questions with diagrams in them. I want to be able to extract them ...
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1answer
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Does YOLO give preference to color over shape or vice-versa while detecting an object?

If you train your YOLO model only on grayscale images to detect car, then would it able to recognise a car in a colored image also. If so, then can I assume that YOLO consider only object shape not ...
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1answer
54 views

Cable angle measurement (rotation)

I need to detect the rotation of a cable (degree) in the x-axis with high precision [0.2 (or more) degree detection] from its original state. Detailed description: I have a cable that is set in its ...
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7 views

Generating HD images - low cost options

I have read online about ways to create HD images using Deep learning. StyleGAN is the the often quoted one. But it very expensive to train on new set of images. It takes around 14 days to 60 days as ...
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1answer
15 views

Retrain Tensorflow CNN Model on additional Images [closed]

So I've created a model to classify images of traffic signs. I'm currently using this model to predict classes of images I've gotten from the internet. However, I would like to be able to re-classify ...
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What is the difference between HLC (Histogram of local features) , CSS ( color self-similarity) ans MDST (Max DisSimilarity of Different Templates)

I'm new to computer vision and have been researching for Master thesis purposes in Detection algorithms and the techniques used in each. As I arrived to the point where alot of papers showed the ...
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Dataset suggestion: video dataset with accurate depth and pose info

Please suggest some datasets (can be synthetic, like rendered in blender or so) which have video frames (30fps preferred) with accurate ground truth depth maps and pose (rotation and translation for ...
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Can reducing the number of classes in multi-label classification increase performance?

This is more of an open question with people which have experience in this. I'm working on a multi-class multi-label classification for chest x-rays. I would like to know how much can reducing the ...
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proper activation function at output and loss function to optimize for OCR?

I am trying to make a CNN model on IAM handwritten words data(which has images of words handwritten by multiple people and targets are text in the images). So, I can encode words to numbers(A=0, B=1 ...
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2answers
26 views

Why are RNNs used in some computer vision problems?

I am learning computer vision. When I was going through implementations of various computer vision projects, some OCR problems used GRU or LSTM, while some did not. I understand that RNNs are used ...
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14 views

Unrelated output by pytesseract image_to_string function

I'm trying to extract text from an image but pytesseract is giving a totally different output, the image attached below output is "Werle" (complete different word and characters), I tried ...
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1answer
29 views

What is semantic gap? Why it exists in AI

The semantic gap characterizes the difference between two descriptions of an object by different linguistic representations, for instance languages or symbols. The semantic gap can be defined as "...
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1answer
95 views

Canny edge detection not working on Gaussian blurred images

I am trying to detect edges on this lane image. First blurred the image using Gaussian filter and applied Canny edge detection but it gives only blank image without detecting edges. I have done like ...
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33 views

Is epsilon error a standard known error or custom created by this paper?

I'm reading this computer vision paper, research paper link, about creating a model to estimate the real age and perceived age of the person in the image (or at least that's what I think it's about). ...

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