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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Synchronizing Multiple Cameras in Autonomous Driving

Please forgive the naivity of this question, it's just due to lack of experience. It goes without saying that self-driving cars have up to 8 cameras and more that do various vision related tasks: ...
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Where can I get Eye Sight Dataset? [migrated]

In my Final Year project, I want to build an AI Application which will scan human eye and recommend suitable focal length glasses according to respective eye sight. Therefore I need eye sight dataset. ...
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How to build a 2-d bayes classifier

I'm working on a 2-d bayes classifier and I'm a little confused on how to start exactly. My attribute space is 2-d. There are 3 classes. The data is assumed to be normally distributed. p(x | y1): P(...
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Scenario description of Roads using Deep learning

I want to do scenario description of road. If there are cars, humans infront of the blind person it should describe the scenario and output should be consumable by blind person. Question: Should it ...
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1answer
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What is the State of the art method for full body gesture recognition in images

I am working on gesture recognition in images and the best way that I am aware of, is whether using end to end approaches with deep neural networks or extracting body joint positions in an image and ...
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Bags of visual words - counter intuitive result

I'm reading the frequently-cited paper Bags of Binary words for Fast Place Recognition in Image Sequences and have found something strange in the paper. The similarity measure is presented as: $s(v_1,...
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Computer Vision model/solution deployment channels

I am very new to computer vision and am currently dealing with ways to deploy a computer vision model/solution for my current company keeping in mind the following factors :- 1)Capability to demo ...
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Fine-tuning a Pre-trained model (Resnet50) do I need to validate it or just train it?

When fine-tuning a Resnet50 model should I do the standard train validation split and train like any normal CNN or should I just do the training and not the validation if I am going to use this model ...
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why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ? and will this lead ...
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13 views

Speed Regulation of fan using Machine Learning

Can machine learning be used for the speed regulation of fan based on the environment, how many people are present in the room and routine of a particular individual and how? How can i achieve this?
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Inconsistent inference results in deeplab v3+

I trained and exported the model as suggested in :https://github.com/tensorflow/models/tree/master/research/deeplab. The validation results saved using vis.py are fine but when I apply demo code for ...
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How to grasp the full entropy of the distribution we want to model in GAN

In pix2pix GAN paper( https://arxiv.org/abs/1611.07004), authors found that the noise vector and the dropout are not efficient in grasping the full entropy of the data distribution we want to model. ...
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Convert YoloV3 output to coordinates of bounding box, label and confidence

I run YoloV3 model and get detections - dictionary of 3 entries: "detector/yolo-v3/Conv_22/BiasAdd/YoloRegion" : numpy.ndarray with shape (1,255,52,52), "detector/yolo-v3/Conv_6/BiasAdd/YoloRegion" : ...
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84 views

Random accuracy results on validation set (Binary classification)

I am configuring a CNN model for a classification problem of human action in Python using TensorFlow. My data is video frames representing human body joints. Every 3 consecutive columns represent x,y,...
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1answer
94 views

Multichannel numpy array to PIL image

I have a 4 channel Numpy image that needs to be converted to PIL image in order implement torchvision transformations on image. But when I try to do this using ...
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How to use machine learning to create combine of opposite images side by side

Inspired by: Two Worlds Pictures I just want to create a Machine Learning Model that can automatically combine the opposite images into 1 image. I am thinking about 2 possible solutions: Pose ...
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1answer
102 views

How to add a new category to a existing trained deep learning model?

i have trained my deep learning model initially with 5 classes now i want to add another class without training the whole model over again for those 5 classes. How can I do that?
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28 views

reverse engineer console game FPS sensitivity for replication

Would it be possible to reverse engineer a FPS games sensitivity/dead zone/acceleration curve/ and other data by recording the games screen and running a controller through a pc to record joystick ...
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Can Microsoft's cognitive service find similar person in a set of images without using the face service?

I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
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2answers
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Which service could I use to train my networks?

My laptop's Intel i7 3630QM 2.4GHZ, 8Gb RAM and GXForce 670M are clearly not sufficient... By reading some papers, I've written an SRGAN with Python Keras. At runtime there is no error but training ...
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3answers
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Computer for DS curriculum

I actually need to decide on which computer I will be taking for a Data Sciences curriculum, including machine learning and further hands on Hadoop. Some computer vision applications are also planned. ...
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Hardware recommendation for FRCNN deep fashion data

I am working a research project to build a FRCNN model for attributes detection using deepfashion data(300K images with 1k attributes). I am struggled on hardware issue with my current training box ...
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1answer
36 views

Reconize a card from a video stream

I want to make an mobile app where you scan using the camera and it gives you the card you just scanned. (from a board game) I got a PNG of each and every single existing cards, but I don't really ...
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219 views

Pre trained dataset for Car damage detection

I'm making a Car Damage Detection model which would have 2 classes to detect upon. My dataset has a total of 300 images (out of which I'd be using some for testing), which are totally insufficient to ...
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1answer
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Unable to understand the meaning of following lines of the research paper for image segmentation

I am implementing a paper on image segmentation. It is based on the slight modification of the u-net architecture. The paper is based on encoder and decoder steps Following are the lines of the paper ...
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21 views

Train CNN-RNN network for multi label video classification with sliding window technique

I’m implementing a model in which a CNN model is used to extract feature sequences from videos , and RNN is used to analyze the generated feature sequences, and output a multi label classification ...
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Atrous convolution allows arbitrary feature map resolution

I'm reading Deeplab paper. In this paper, the authors proposed to use atrous convolution, whose 1-D form is: $\hspace{3.0cm} y[i] = \sum_k x[i + r \cdot k] w[k]$ Given this scheme, they wrote that ...
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1answer
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Saving images in a non-retraceable way, but still able to train R-CNN's on them

For a computer vision project I am working with images that the company only allows me to have on my computer for a maximum of 24 hours due to regulations. Every day a few hundred images come in via ...
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2answers
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Pre-trained models

I am starting off with machine learning so could someone tell if there is some site where one can find the current best performing trained models for any specific problem like sentiment analysis or ...
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1answer
40 views

What is “spatial feature encoding”? Can anyone give a concrete example?

This book "Deep Learning and Convolutional Neural Networks for Medical Image Computing" mentioned a term spatial feature encoding On the other hand, CNN models have been proved to have much higher ...
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48 views

How to calculate size and offset of YOLO grid in a fully convolutional network with zero padding?

Fully convolutional network with zero padding: I have a fully convolutional network which does not have any padding in convolutional layers. This implies that, after each convolution operation, the ...
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1answer
90 views

Comparsion between DCGAN and WGAN

What is the main architectural difference between DCGAN and WGAN? For which problems each models can be more useful than the other one?
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1answer
125 views

What model should I use for bounding box detection?

I am working on building a cow detector for a local farm. I have a dataset of images with bounding boxes (not segmentation polygons) for every cow appearing in the images (different number of cows in ...
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1answer
20 views

Quickest way of multi-labelling images?

I want to make a new dataset containg thousands of (different-sized) images. Now I need to assign multiple labels to each image. Of course I already looked at github etc. and there are good labelling ...
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2answers
29 views

Keras Model question for Pre trained model extension

I want to add a few more layers to a Resnet50 model and my question is - do I need to compile it and train it on new data or can I just use it as it is? Will it just give me the Resnet50 results? ...
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2answers
142 views

Looking for animals dataset for deep learning classification

Do you know any datasets that contain animals and their accurate classifications? I am looking for any dataset that categorizes animals. For example: a dataset with insects, with an image of an ...
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Best OCR approach on documents with different formats to find one specific information

Unfortunately, because of confidential data, I can't give a more specific explanation. The Problem So I've got a few documents that in general contain the same information but have different formats....
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Help needed implementing Convolutional Sequence-to-Sequence Network

I am trying to build convolutional Sequence-to-Sequence network that takes inputs (satellite images) and predicts the next sequence of images. As a result, we can then predict the weather. I have ...
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1answer
22 views

Is text recognition by definition a part of image recognition?

I'm referring to more advanced text recognition systems that are using neural networks to find and extract text from images like the ones Google and Microsoft are offering on their ML platforms. If ...
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8 views

Automatically assess training data quality for land cover classification system

I am working on a Land cover classification system, wherein, Sentinel-hub imagery is being used to categorize the land cover by using a time series of multispectral imagery. Training data is being ...
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Should detection times get longer for dlib.train_simple_object_detector when I add more images?

I've played around some with dlib.train_simple_object_detector and have found that as I add more images the detection time grows longer when I later perform detections. Why is this happening? To my ...
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How to find the False Positives per Image when using the Tensorflow Object Detection API

I have trained a Faster-RCNN Model using the Tensorflow Object Detection API on a custom dataset consisting of 10 classes. I have evaluated its performance and obtained the mAP and AP for each class. ...
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61 views

NCHW vs NHWC in Machine Learning

As I've been introducing myself to the various deep learning frameworks, I've noticed a difference in the default placement of channels for images. Is there a substantial difference between NCHW vs ...
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Image and Video Formats with lossy-compression and fast subregion lookup?

I'm looking for image / video file formats that support lossy compression to reduce disk size and allow for fast subregion lookup. i.e. dont read the entire file when you only need to lookup a small ...
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1answer
489 views

Creating a Object Detection model from scratch using Keras

I have a dataset containing 330 images which contain guns. Along with the images, I have a text file associated with each image file which contains, The number of objects ( guns ) in the image. ...
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Hardware for deep learning [closed]

Disclaimer: I am very new to using stackexchange so bear with me. I am trying to gain experience using neural networks and would like to do a few projects involving them. Right now I am trying to ...
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2answers
59 views

Manually creating plants images dataset for machine learning plant type classification and leaf segmentation

A group I work with wants to create its own plants data set that will be used for multiple projects like plant type classification and leaf segmentation for starters. They are willing to provide all ...
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1answer
540 views

What is the difference between semantic segmentation, object detection and instance segmentation?

I'm fairly new at computer vision and I've read an explanation at a medium post, however it still isn't clear for me how they truly differ.
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Is it possible to modify the layers of the models present in the Tensorflow Object Detection API

I would like to know if there is any way in which we can change the base layers of the models offered by the Tensorflow Object Detection API and if so, is it possible to change things like pooling/...
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Face recognition - How to make an image classifier with large number of classes?

I am planning to make an image classifier that identifies the face of every player in the English Premier League. I have a couple of questions (since until now I have only worked with small or ...