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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Auto-Encoder/Decoder - Generic Swapping Model

I'm just starting out in ML and I am interested in a model that can swap similar things in images, like doors or items on a desk. Is it possible to take a library like https://github.com/deepfakes/...
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How do you classify multilabels which may be related to each other in some way?

I am having a hard time wrapping my head around training a multilabel classifier where the different outputs have some relationship among themselves. For example, if I were to try create a model to ...
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Model does not learn after ternarization of weights contrary to the paper mentioned below

I’m implementing the ‘Ternary Weights Network’ paper by Fengfu Li and Bo Zhang ( archive link - https://arxiv.org/abs/1605.04711). I’m training a simple Covnet with linear layers on the MNIST dataset. ...
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Where can I find windows environment image dataset?

I'm looking for a dataset of windows environment images labeled with main windows elements like window, taskbar, close button, etc., independent of the Windows version. Is there any? Edit: something ...
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name 'layers' is not defined [closed]

I am trying to use EfficientNetB7 from keras implementation Image classification via fine-tuning with EfficientNet but always the following code gives me error: ...
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Why a CNN with decreasing filter layers sizes could perform better than a "regular one" with increasing sizes?

I did dozens (or probably hundreds) of tests and the best result with less total parameters(4 times or less) was a decreasing filter layers size architecture. This is a CNN for multiclass image ...
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How to handle the case of multiple ground truth boxes having high IOU with the same predicted box?

In single shot detector the matching strategy between ground truth and predicted box starts with the following step: For each ground truth box we are selecting from default boxes that vary over ...
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3D object detection for 2D images (logistics use case)

I am working on 3D object detection for parcel boxes same like amazon parcel,thinking to label with 3D cuboids but finding difficult to find a existing 3D object detection for 2D images. As far what i ...
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Error parsing message with type 'tensorflow.SavedModel'

This is the error message i get- ...
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Reducing Tensorflow model prediction time

My Tensorflow object detection (faster RCNN) model is taking ~6 sec to predict. Can anyone let me know how can I make prediction time to millisec without compromising on accuracy My system ...
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DeepSORT's Feature extractor cannot be used for Person ReIdentification

I am using this repo for DeepSORT - https://github.com/nwojke/deep_sort I am trying to build a Multi Camera Person Tracking system. I want to save and utilize the features extracted by one camera in ...
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how to train image classification with small difference in low-level feature

I would like to build the model that capable of doing classification for example 2 classes below : I tried alexnet, resnet50, resnet18, vgg16 but seem they are failed to differentiate between this ...
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How to benchmark own model trained by Yolov5

I trained a model with my dataset for object detection - using 1500 samples. Now I'm not pretty sure how to benchmark my model. What is the procedure before using the model? Are the parameters in the ...
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Tensorflow model structure is strangely deformed in model.fit()

I was able to confirm (by checking model.summary()) that a model with the correct structure was successfully created. However, when ...
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How to label motion video data?

I am building an Arabic sign language dataset. How to label many frames of a video to detect the full motion? (like the following gif) So when I do it again the model understands the sign I only ...
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How do you train a semantic segmentation model to optimize for IoU rather than accuracy?

I am currently building a U-NET semantic segmentation model on Tensorflow Keras to classify pixels as belonging to or not belonging to a class. For this problem, I've isolated the masks for only one ...
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Instance segmentation - Which is the best approach for my use case?

I am looking to train an instance segmentation model that will be running on the edge, like on mobile devices. What is the best network (Mask RCNN, DeepLab v2/3 etc.) for this use case? Which gives ...
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When should one train YOLOv5 on custom dataset or use standard COCO weights?

I am running a YOLOv5 detector on the below video to detect persons in the stream. It is giving me satisfactory response. I need to know if I should train the model on my custom dataset, or continue ...
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Why is my training loss not changing?

I'm trying to train a semantic segmentation model based on this architecture, using this one as a base. The base model uses about 10 ReLU activations, and when implemented according to the first paper,...
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Privacy Aggregation of Teacher Ensembles - Object detection

Does anyone know how PATE(Privacy Aggregation of Teacher Emsembles) can be applied to object detection? This becomes quite complex since we're dealing with possibly multiple objects detected in the ...
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What is the best Panoptic Segmentation algorithm up to date?

A Cityscapes ranking would suggest that EfficientPS and Panoptic-Deeplab are the best, while the Coco ranking suggests other algorithms, more recent, like mask2former. Which one is the best?
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Scaling the output of a segmentation model (UNet)

So, I have to solve an instance segmentation problem and I am thinking of implementing a UNet model based on Ronneberger et. al. 2015 paper. The problem I have is that the output size has to be ...
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Object detection or image classification? Each image has 3 shapes. I want to return 1 if they are all triangles, 0 otherwise

Question is in the title. Every image has three shapes, which can be either triangles or squares. I want to return 1 if all shapes are triangles, 0 otherwise. Which do you think would work better for ...
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Increasing training accuracy of U-Net segmentation model

I was working with segmentation using u-net and MobileNet. While I trained with input size 256*256 it had an output with Val loss: 0.044 (In this time dense layer was 256, 128, 64, 32 with a learning ...
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Can I send images + boundingboxes(as features) to an LSTM? How?

I have previously trained a YOLO v4 object detection model and I am looking to leverage the results(Bboxes) of this model and create another model to recognize/classify accidents in CCTV footage/video(...
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1answer
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error: (-215:Assertion failed) [closed]

I was testing OpenCV with their code provided within the documentation. Unfortunately, I'm facing an unexpected error. I think, it might be due to the newer version that I've. I've tried the fix of ...
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Increase accuracy through "overfitting" multiple models?

I am currently trying to create a model to classify 5 specific classes from the coco dataset. I am using the object detection app from tensorflow. My question is: Will it be better if i: -Train one ...
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Difference between the architectures of semantic and instance segmentation

My question is about the difference between the architectures of semantic segmentation and instance segmentation models. So, as far as I understand, a semantic segmentation model is making pixel-wise ...
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Is Hough transform an appropriate line detector for my problem?

I try to get automated labels for images with the help of computer vision. Problem The labels are papyrus fibers on the outer edges of a papyrus fragment. After some research (for example [3]), I come ...
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Convert from gray to BGR

I want to convert my grey mnist to color. I have came up with the following code, but the output is still gray. ...
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spot/stain growth in image classification problems

I am working on a problem with images where we are monitoring development of spot in certain region of image. We are able to classify spot present(NOK) or not present(OK) successfully if initially ...
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Is it possible to apply a time series generator to a image data generator?

I have the following code: ...
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Need help in understanding how YOLO works?

In YOLO's original paper, I am quoting the parts I dont understand: Our system divides the input image into an S × S grid. If the center of an object falls into a grid cell, that grid cell is ...
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Unstructured data not template based to structured data

I am working on a project where my goal is to extract data from a large diversity of pdf that does not follow a template (i.e unstructured data not template based). My ORC part works well and now I am ...
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How to make an DL model predict Correctly [closed]

So I trained a DL algorithm using Keras for Human Action Recognition. The model has an accuracy of about 85 percent and a loss of 0.3 something. The problem is that the model did not predict well on ...
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What is `Multi-scale` in Multiscale Convolutional Network?

I was reading an article on Deep Learning and came across this term called Multi-scale Neural Network. I fully understand the concepts of convolutional neural network but it is a bit difficult to ...
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Machine learning roadmap not for beginners [closed]

To introduce myself: I know what is RL, know some RL algorithms such as PPO, A2C. Know about offline RL, online RL. I have read many papers about RL. Such as MuZero, AplhaZero, Decision Transformer ...
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Is there any way to remove background of an image fully with the help of post-processor techniques(like edge detector) after deep learning based model

I'm using a deep learning model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image is a person. And my target is to extract the ...
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Deep learning / computer vision technique: aggregating many input images to a single representation of the features within

I have a few thousand grayscale images, and I would like to generate a universal representation of the patterns within - a semantic/ordered composition of all features, so to speak. For instance, take ...
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1answer
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Error during the compilation of a neural network in Vitis AI, "Not found op in super_const_dict: name: Decoder_Section_1_UpConv_1/kernel"

I'm following a Xilinx Tutorial about the implementation of a Neural Network in a System on Chip (ARM Processor + Xilinx FPGA) and I have come up with an error during the compilation step. I've ...
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1answer
246 views

Computing F1 score for YOLOV5

I am confused at finding out the exact F1 score of my YOLOv5 model which underwent training for 150 epochs. Also, how can I know if the model has done well based on these graphs? Here are the metrics: ...
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Soft-NMS during Inference

I have read the paper about the soft-NMS and the problem that tries to solve. Does it make sense to use this algorithm during inference apart from training? It smooths the predictions on the bounding ...
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1answer
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Data Art/ Data Visualization Art/ Information Art

Few days ago, I learned about data art/ data visualization art/ information art. I think I have interest in it. I want to see how I can use my data science skills in this area. However, I don't know ...
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How can I detect symbols/icons on a label?

Given this label: How can I identify that the CE mark is there? I've tried template matching with OpenCV but results are quite inconsistent because of symbol-template size differences (scaling & ...
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1answer
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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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Why does my Yolov1 output tensor contains negative value?

I have been working on my own imlplementation of the Yolov1 model. The first thing I want to mention is that It seems to be learning. Here is the train/val curves : (<0.1 train and 0.26 val loss) ...
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overfitting in captioning model

Train 8000 images Val 1000 images i got this plot for 10 epochs with the last one which is ...
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Identify areas within a shape/polygon with Vision / ML

Given a shape, in the format of a binary image, I would like to detect and subdivide it to new areas. Below is an attached example of such a shape and the expected outcome where each new area is ...
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Developing a deep learning hybrid architecture for a particular problem is a highly complicated task [closed]

I am currently conducting research on application of deep learning (sensor signal recognition). I spent about a year and a half sifting through the literature and discovered some research patterns. To ...
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How to read video dataset in tensorflow/keras?

I'm trying to develop simple 3D-CNN network for the task of video classification. I'm having 6 categories with 100 videos for each category. How can I pre-process this data and feed to the model? And ...

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