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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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Using a discriminator to distinguish ground truth and predicted boxes for FRCNN

We have implemented an object detection framework in Keras based on the Faster R-CNN model. Currently, we would like to find a way to automatically classify images on which the model is performing ...
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1answer
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How to detect different brands of milk

I'm trying to create a object detection model to detect different type of milk. What is the best approach to achieve the result in the picture below? As you can see in the picture, this model did ...
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Identify credit card shape using machine learning mobile

I have asked a previous question related to identifying and Isolating credit card from background here I was able to get a good model to work on Desktop/Laptop systems using semantic segmentation. ...
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Is there any argumentation tool for images and bounding boxes?

I don't have a lot of training data and I'm looking for some tools in python or executable program like labelimg that do some heavy argumentation on images, even better if they also change bounding ...
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1answer
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How can I detect blocks of text from scanned document images

ORIGINAL IMAGE: GOAL: I want to separate texts into individual paragraphs by placing bounding boxes over them (as shown above). I tried it do this via traditional computer vision approach using ...
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1answer
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what is the best approach to detect small objects with similar shape?

I'm working a model which detect different products in supermarket shelf. In the training data, there are a lot of objects with similar shape placed very close to or stacked to each others.(eg: milks ...
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How can I detect partially obscured objects using Python?

I'm building a computer vision application using Python (OpenCV, keras-retinanet, tensorflow) which requires detecting an object and then counting how many objects are behind that front object. So, ...
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1answer
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How to determine key frames in a video for video classification?

How to detect changes between when the changes between 2 frames of videos that are significant enough to be counted for video classification? Thinking of the problem as analogous to edge detection in ...
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1answer
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How to detect blocks of texts in document images

I am planning to detect texts from document text images like below: GOAL: WORK DONE: I have tried to solve this with some scene text detection algorithms like EAST Text detector and PixelLink. But ...
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1answer
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How to generate Anchor boxes for SSD?

I am currently trying to understand the method of generating anchor boxes for object detection. I am looking at a code where the author has done this task in a very flexible way. But I am having ...
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2answers
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3D point reconstruction from 2D images

I know this must exist, but I'm having enormous trouble finding the right search terms. Say I have a bunch of labelled 3D points, and I capture multiple 2D images of it. If I want to reconstruct the ...
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1answer
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Approach fpr extracting/cropping features images using deeplearning and no annotations

Let's say I want to have a bunch of images of hats from videos. How would I priniciple build something that would learn to recognize, and crop or bound box hats? I heard you need a dataset with ...
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How can I find a large dataset of medical images for cancer classification [migrated]

I am looking for a large image dataset >20K to be used for cancer classification algorithm. Where can I look given that all public available datasets are maximum 1K in size which is much less than ...
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How to determine frame rates to detect for video classification [closed]

I am building a Deep learning model for vibration, I have video inputs and I want to analyze this video for vibrations and categories these vibrations into various classes of vibrations, what ...
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1answer
192 views

cv2.error: OpenCV(3.4.3) (-215:Assertion failed) !empty() in function

Would anyone have a tip on how to fix this empty function error in OpenCV? I am attempting to follow the guides on OpenCV.org The script will detect a face in an image and draw boxes around ...
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1answer
31 views

Calculate image width

In this code below, a picture can be loaded into openCV and then the region of interest RIO can be created by just selecting a box around something with the mouse, then press ...
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26 views

openCV tracking algorith & Haar Cascades

(long question sorry) This script below will utilize my windows 10 laptop webcam detect faces with haar cascades and calculate the centroid of what ever is captured. Besides OpenCV I also use the ...
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YOLO: how are outputs generated and how are feature maps used?

I've been looking into YOLO algorithm and couldn't understand how the final output is made. It seems that training YOLO requires the following information: Grids that are divided into a size of S x ...
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Detecting blinking light on a device

Can anyone tell me good approaches to detect blinking light in a video? The background may change constantly. As of now, the color would remain same but the intensity and angle of vision can change. ...
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A noise robust Local binary patterns variant

I’m thinking of using Local Binary Patterns (LBP) to extract features from MRI images of brain tumours to build a module for classification, due to its computational simplicity and good performance, ...
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2answers
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Pre-processing on MRI images

I have MRI images of brain tumors collected from a hospital (not a benchmark dataset). And I am planning to use them to predict/classify tumour types using a typical machine learning approach: texture ...
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What is the most efficient method to detect drowsiness?

What all parameters other than face detection, speed and steering variations, yawning frequency can be used to detect drowsiness? What method is more efficient in drowsiness detection? What ...
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1answer
105 views

how to apply similarity algorithm(or comparision) of over one million vectors with other one million vectors?

how to apply similarity algorithm(or comparison) of over one million vectors with other one million vectors Please help I am a beginner in this field I am following this pyimage search tutorial but ...
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1answer
78 views

Machine learning PhD Interview technical questions [closed]

I'm Software Engineer who applied to grad school for Machine Learning/Computer Vision PhD and currently waiting for interview calls. I'm brushing up Linear algebra/ ML topics. What kind of technical ...
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1answer
111 views

Uniformity of color and texture in an image

I am new to the field of deep learning and have a problem in determining whether two images have uniform color and texture. For example, I have a Master image - Now, with respect to this image i ...
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1answer
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Mask RCNN: Random predictions during inference for the same image

I recently trained the Mask RCNN (matterport's implementation) on some satellite images, but during inference mode, I'm getting random predictions for the same set of weights for the same image. That ...
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2answers
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Analyzing Videos using Deep Learning

Is there any work done on analyzing sequence of frames from a video using Deep Learning techniques? By "analyzing" I mean like memorizing them in order to classify or predict something (e.g. by ...
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1answer
154 views

Keypoint matching using HoG and SIFT

I have two images and I've found their keypoints using sift keypoint detector, Now I have to match their keypoints with HoG features, I know how to extract HoG description, but I dont know how to ...
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Fluctuating Learning rate in tensorboard

I am trying to train an faster rcnn for object detection. While I am trying to fine-tune the object detection network I am seeing my learning rate is fluctuating even though I didn't change it. The ...
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Recognize polygons and get coordinates on transparent image

I have to implement a program to recognize polygons on transparent images, like this: So, in this picture we have 4 main polygons, we need to recognize them with a blue background and more dark blue ...
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Using tensorflow object detection in another model

I am trying to use Tensorflow (tf) object detection API models in another custom model I built. Specifically, I am trying to do: jointly train tf object detection models Y with another model X. in a ...
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Sub-Object Attention models

Questions first: I need help to focus myself on the most relevant attention model papers (Attention to Attention if you will). Where should I start? Have you heard of attention models that focus on ...
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1answer
65 views

MR images segmentation for feature extraction

I have datasets of brain MR images with tumours, the tumours are already selected manually by a physicist using Image J. I have read about segmentation, but I still couldn't understand how do they ...
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1answer
19 views

Feature selection/reduction techinique for combination of features in image processing

I have a combination of features extracted from 3 descriptors, namely GLCM based feaures(correlation, homogeneity,energy and contrast ), Local binary patterns (256) and discrete wavelet transform ...
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segmentation of brain tumor in MRI images

I have a dataset of brain tumours images. and I have to build a model to classify the malignancy grade of these tumours. The size of the tumours varies from small to large. The ROI are already ...
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1answer
196 views

cross validation for small dataset

I have a dataset of 39 medical MR images, and I have to build a model to classify the tumor type. so is it suitable to use k-fold cross validation for validating the model? if so, what would be the ...
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1answer
27 views

How would you a apply a cnn to do age estimation on static images? [closed]

After doing some reading on age estimation using the IMDB wiki dataset I wanted to try it out myself on a smaller scale but I dont quite understand the application of the CNN. Any clarification would ...
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2answers
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Autonomous evalution

Do you think it is possible to learn the app, how to autonomous evaluate good or bad parking of the bikes? The thing is you need to take a picture with your phone and app need to decide according to ...
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Equivariance vs Invariance in Convolutional Neural Networks

Could someone please explain to me in details (possibly from mathematical point of view) what is the role of Equivariance and Invariance in Convolutional Neural Networks, and how are they actually ...
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OCR on striked-out text

I have the following image with me: I want to identify the text, which is the amount mentioned at the bottom of the table. However, the bottom edge of the table goes through the text in this case. ...
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how can I get the original pixels that lead to the decision in CNN ? is that possible?

I work on medical images, I want to locate the most relevant regions of the image based on deep learning spatially CNN, so I feed my data into VGG16 architecture, I get the features maps, now I want ...
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1answer
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YOLO pretraining

I'm implementing YOLO network and have some questions. In the original paper the authors say: "For pretraining we use the first 20 convolutional layers from Figure 3 followed by a average-pooling ...
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Training detector without bounding box data

From what I can see most object detection NNs (Fast(er) R-CNN, YOLO etc) are trained on data including bounding boxes indicating where in the picture the objects are localized. Is there any model ...
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1answer
61 views

YOLO layers size

According to the original paper, the input size of the YOLO network layer is 448x448x3 and after the filter (7x7x64-s-2) is applied the output shape is to be 221x221x192 as I suppose. Some sources ...
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1answer
251 views

Bounding box coordinates prediction

How to pass multiple bounding boxes coordinates to CNN model?My goal is to predict the coordinates of texts in an image.
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1answer
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How to train object detection system for 2 classes having two seperate datasets for each class?

I have dataset of class A and a dataset of class B. However dataset A does not contain annotated class B and vice-versa. Is there a way to somehow train object detection system like SSD to detect ...
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237 views

Examples for multi-input Convolutional Neural Network

I want to create a multi inputs Convolutional Neural Network (cnn) that takes two inputs and produces one output of the inputs class by using Keras. I searched for resources that explain multi inputs ...
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1answer
185 views

How to visualize image segmentation results

I am using u-net to do semantic segmentation for N>1 classes. The input size is (128,128,3), the output size will be (128,128,N). what is the correct way see the prediction as an image ot size n1 x n2 ...
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1answer
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What exactly does the model generation mean in this diagram?

I've been trying to grasp a research paper on image colorization using neural networks here I am stuck at this diagram. What I need help on, is the Model Generation step after Feature extraction. ...