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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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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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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 ...
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I can not find a pre-trained neural network model for object detection

A simple model is needed, but with good accuracy, mAP for detecting objects is preferably trained on COCO, preferably on ipynb (to run or train on google colab). The models from the Tensorflow (...
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How to change the neural network model to improve the accuracy of mAP without learning from 0, but retraining already trained model

how you can change the Faster R-CNN Resnet 101 or Faster R-CNN Inception Resnet V2 model to improve the accuracy of mAP detection without learning the model with 0, but retraining already trained ...
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How do I change the IOU while running the eval.py script using the Tensorflow object detection API

I have trained a FasterRCNN_Inception_Resnet_v2 model using the TensorFlow object detection API on my own custom dataset. I am successfully able to evaluate the performance and get the AP of each ...
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fast fourier transformation on images — python

I did Fast Fourier Transform on lena image and I would like to extract real and imaginary parts of its spectrum. This is my code: ...
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Transposed convolution as umpsampling in DCGAN

I read several papers and articles where it is suggested that transposed convolution with 2 strides is better than upsampling then convolution. However implementing such model with the transposed ...
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memory error while converting images into an array

I am working on a facial recognition use case. I have 57k jpg images and am converting them into an array. While executing the program, I am getting a memory error. The function I am using: ...
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I am building a gesture recognition system using video data from ConGD Dataset and am not able to create the 5D array,as input to the network

I need a 5D input for my network using ConvLSTM and 3D-CNN. Converting the videos to an array of videos would contain a 5D array (Num of examples, Num of frames, FrameWidth, FrameHeight, NoOfChannels),...
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Is it possible to measure the object using deep learning

Is there a way we can measure the length, width and the depth of an object in the picture using deep learning?
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Detecting unique icon on video in real time

For a project I am working on I'd like to be able to detect unique icons/barcodes in video footage. Suppose you have 10 people in the frame where each person is wearing a t-shirt with a similar but ...
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What is fractionally-strided convolution layer?

In paper Generating High-Quality Crowd Density Maps using Contextual Pyramid CNNs, in Section 3.4, it said Since, the aim of this work is to estimate high-resolution and high-quality density maps,...
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How to calculate Average Precision for Image Segmentation?

If I've understood things correctly, when calculating AP for Object Detection (e.g. VOC, COCO etc) the procedure is: collect up all the detected objects in your dataset sort the detections by their ...
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Microscope Image Denoise

Hi I'm working in a computer vision project, basically, the goal is to detect some specific parasites, but now that I have the images I noticed that they have a watermark that specifies the microscope ...
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Cannot Obtain Similar DL Prediction Result in Pytorch C++ API Compared to Python

I have trained a deep learning model using unet architecture in order to segment the nuclei in python and pytorch. I would like to load this pretrained model and make prediction in C++. For this ...
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Which learning tasks do brains use to train themselves to see?

In computer vision is very common to use supervised tasks, where datasets have to be manually annotated by humans. Some examples are object classification (class labels), detection (bounding boxes) ...
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Should images with multiple objects of the same class be used as training sample for multi-classes object detection models?

Let's say the model try to detect all the grapes on a branch of grapes. Can I use images of a grape branch with all the grapes labeled as a training sample? Will it affect the quality of the RPN ? Is ...
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What is the difference between “offline trained model” and “pretrained model”?

I am confused that both are same or not, and then how can I differentiate with the online training model.
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What is Coarse-to-Fine in the context of neural networks?

I read in many paper that mentions coarse-to-fine as a technique in deep learning, but I could never figure what exactly they mean. Is it related to multiscale inference, where they use coarse and ...
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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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2answers
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Is there any augmentation 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 augmentation on images, even better if they also change bounding ...
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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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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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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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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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181 views

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

How can I apply similarity algorithm (or comparison) of over one million vectors with another one million vectors? I am following this pyimage search tutorial but don't know how to scale up the ...
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1answer
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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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336 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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308 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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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 ...