Questions tagged [object-detection]

For questions related to object detection (where objects can be e.g. humans, dogs, houses, etc.), whose meaning or definition can vary depending on the context. OD can refer to the task of locating (i.e. finding the coordinates) an object in an image (so, in this case, it would be a synonym for object localization) or the task of locating the object and classifying it (i.e. object localization + object classification).

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Advanced Techniques for Feature Detection in 3D Models with Overlapping Features Question:

I'm working on feature detection within 3D models (given only points and lines forming areas), specifically focusing on extracting detailed information (e.g., corner coordinates) of complex features. ...
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29 views

Does roboflow tool annotate the images correctly?

I have started working Helmet Detection problem and decided to train the YOLO model. The very first step is to get a good quality dataset, which I found here on kaggle. The total number of images is ...
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162 views

How to reject boxes inside each other with Non Max Suppression

I’m working on an object detection cnn, and having some issues with non max suppression. When I have a small box inside a large box, NMS is not rejecting the smaller, incorrect box, because its IOU is ...
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18 views

Object detection with deep learning

I am getting familiar with video detection/tracking using neural networks. Specifically, I am referring to algorithms that take in input an image or a sequence of images and, for each frame, it ...
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1 answer
37 views

How to automatically trigger model retraining for object detection models in case of data drift?

I have fine-tuned a pre-trained Yolov8 model on my dataset of labelled containers in a warehouse conveyor belt (image example here) . I am working to develop an MLOps project for my project portfolio, ...
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2 answers
103 views

How to detect negative (absence of) an object?

I want to detect the people that are NOT wearing PPE vests using a pre-trained object detection model like YOLO or Grounding Dino. The models are able to detect people and vests separately, but I am ...
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1 answer
96 views

YOLOv3 Synthetic Data Training

Suppose we want to train a model to detect various objects. Let's say we have training data of those objects in various backgrounds along with their bounding boxes. Basically these objects have been ...
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2 answers
750 views

For an image (of any object), how to find its location in the other image(s) which contains it, given there are no labels or annotations for any image

Problem Statement: I am given 2 sets of images. All the images in both sets are without annotations and labels. First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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2 answers
365 views

What does a value of -1.000 mean in MS COCO Metrics for Object Detection

I am training some Object-Detection-Models from the TensorFlow Object Detection API and got from the evaluation with MS COCO metrics the following results for Average Precision: IoU = 0.5;0.9 maxDets =...
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1 answer
261 views

Role of confidence or classification score in object detection mAP metrics

I know that mAP (mean Average Precision) is the common evaluation metric for the object detection tasks. It uses IoU (Intersection over Union) threshold such as [email protected] to evaluate whether the ...
1 vote
1 answer
98 views

Are there any good ways of simultaneously incorporating object detection with speech recognition?

Are there any good ways of simultaneously incorporating object detection with speech recognition? For example, if you want to identify whether an animal is a dog or cat, we can obviously use visual ...
2 votes
2 answers
127 views

Recognition of lines in a chalkboard

I'm trying to develop a real-time application that, from the sequence of chalkboard images captured by a webcam, recognizes the lines being draw on it. It must be able of recognize the lines from ...
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2 answers
87 views

Performance of augmented dataset with or without original images

I am training on yolo and I had a small dataset. I decided to increase it by augmenting it with rotation, shearing, etc to increase the size and increase accuracy. Now I have seen augmented datasets ...
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1 answer
939 views

In Faster R-CNN, how can I get the predicted bounding box given the neural network's output?

The RPN loss in Faster RCNN paper is $$ L({p_i}, {t_i}) = \frac{1}{N_{cls}} \sum_{i} L_{cls}(p_i,p_i^*) + \lambda \frac{1}{N_{reg}} \sum_i p_i^* L_{reg}(t_i, t_i^*) $$ For regression problems, we have ...
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2 answers
34 views

Should I define my problem as image segmentation or detection?

I have a problem and have to decide wether it's an object detection or object segmentation problem. I want to use Yolov8 for training. We already have hundrets of images but they aren't labeled yet. ...
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1 answer
353 views

Object Classification: How to decide which detected region is a RoI for classification?

I am working on a project where I am working on the Flickr-47 dataset to do logo detection and classification. My approach is to first finetune a YOLO v5 model with high recall to detect as many "...
1 vote
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68 views

Ways to train a neural network continuosly as new data is added [duplicate]

There is a project I'm currently working on that requires object detection with continuous training. The idea is to train a model beforehand with a standard dataset. When I get new images I want to &...
7 votes
1 answer
2k views

What are the differences between Yolo v1 and CenterNet?

I recently read a new paper (late 2019) about a one-shot object detector called CenterNet. Apart from this, I'm using Yolo (V3) one-shot detector, and what surprised me is the close similarity between ...
2 votes
3 answers
634 views

Face liveness detection using face landmark points

How to detect liveness of face using face landmark points? I am getting face landmarks from android camera frames. And I want to detect liveness using these landmark points. How to tell if a human ...
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1 answer
122 views

Keypoint generation in 3D point clouds with Deep Learning

I have a huge dataset of 3D point clouds (each point consists of X,Y,Z coordinates) and another dataset with keypoints (also X,Y,Z) which lie on quite recognizable structures in the point cloud. As a ...
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1 answer
113 views

How vision models based on CNNs learn the relative positions of each pixel in the image?

A CNN model is based on a series of filters applied to an image. However, these filters can only "see" a small portion of the image and they have no information of the relative position of ...
1 vote
2 answers
209 views

What kind of algorithm or approach can I use to find a specific type of object in an image?

What kind of algorithm or approach can I use to find a specific type of object in an image? In particular, I am interested in finding an object like a windmill in an image taken, for example, from ...
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17 views

kerascv retinanet for gender identification

I am using KerasCV Retinanet to detect people and their genders in images. I would like to detect "man", "woman", "boy", "girl" and "baby" in images. ...
1 vote
1 answer
43 views

NN Architecture for the detection of "sparse" Objects

I have a document digitalization task where I want to detect technical drawings from images. These Images mostly consist of objects made up of combination of shapes like lines, circles and rectangles. ...
1 vote
1 answer
114 views

What are the state-of-the-art Person-Detektion / Human-Segmentation?

I would like to use a deep learning approach to detect people in videos. I have found some freely accessible implementations like Human Segementation with Pytorch or BodyPix / DeepLab / Pixellib with ...
1 vote
1 answer
1k views

How does YOLO detect the object when the object is in multiple grid cells?

I have been reading various articles and watching videos on YouTube, but I can't seem to understand one thing. How does YOLO make a bounding box for an object if it is in multiple grid cells? For ...
1 vote
1 answer
379 views

Mask R-CNN: How are the computed masks projected back to the input image?

The computed masks by Mask R-CNN are of fixed size $m \times m$ each. How are they projected back to the image?
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2 answers
655 views

How to count overlapping objects with neural networks

Consider the following task to be solved by a neural network: Given a $N\times N$ pixel grid with up to $M$ objects drawn on it, either squares (9 pixels) or diamonds (5 pixels): square    diamond The ...
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2 answers
90 views

How to measure classification accuracy in object detection task?

Object detection uses mAP as the metrics. But if we are only interested in classification once the object in a bounding box is extracted, what metrics should we use? Thanks!
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1 answer
436 views

How to extract the high-level features of YOLOv5?

I am faimilar with extracting the high-level features from any pretrained model for classification problem such as ResNet version, VGG, etc. It is easy to extract the features because there is a fully ...
1 vote
1 answer
765 views

How do I perform object detection if there is only one type of object?

How do I do object detection (or identify the location of an object) if there is only one kind of object, and they are more of less similar size, but the picture does not look like standard scenes (it ...
0 votes
1 answer
81 views

Transfer learning using pretrained tensorflow object detection model [closed]

I am new to AI/ML and wanted to seek guidance as I am totally lost. I will simplify my issue as follows: Let's say I would like to detect apples and oranges in images. I would like to leverage a pre-...
5 votes
4 answers
658 views

Can bounding boxes further improve the performance of a CNN classifier?

Suppose I have a standard image classification problem (i.e. CNN is shown a single image and predicts a single classification for it). If I were to use bounding boxes to surround the target image (i.e....
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22 views

Building an algorithm that detects an area delimited by a quadrat

I want to build an algorithm that takes an image and outputs the same image, but cropped so that it focuses only on a particular area delimited by a quadrat, like so: This is not my image as I am not ...
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16 views

YoloV5 Calibration

I'm currently tackling the task of calibrating object detection models specifically tailored for medical imaging applications. Despite extensive online research, I've encountered difficulties in ...
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23 views

Yolo object detection metrics

I have made some predictions and saved the results to YOLO format. Then I made a program to calculate metrics, every metric looks fine except Precision/Confidence curve. I guess the flatline at the ...
1 vote
0 answers
33 views

Advice required for identifying bone fragments in CT-scans using STL Files (3D image segmentation)

I am working on a project related to automating the procedure of manually segmenting some bones in CT scans and hopefully if everything goes alright in this stage, move on to do something more with ...
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66 views

Model architecture object detection where entire image context and nearby objects are important to accurate prediction

I'm working on a model to classify multiple extremely similar looking objects in a single image. A simple object detection model works ok but the issue is that I'm classifying similar looking object ...
1 vote
1 answer
110 views

How to ensure continuity of AI model logic?

I am aware that this question might be vague but I must try anyways. I am looking for a method or an algorithm or even just some keywords (to conduct further research) of how to deal with phenomenon ...
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1 answer
129 views

Why YOLOv7 not detecting small objects

I am using YOLOv7 trained on custom dataset, and using the model weights after converting to ONNX for CVAT annotation. There it's only predicting few small objects. Is there any limit on small object ...
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127 views

Use AI/Computer Vision to detect scene changes

I'm trying to use AI and computer vision techniques to identify scene changes for a camera. Something like this: What are some approaches to do this? Any ideas? The scene is static. Somewhere I saw a ...
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18 views

Meaning of Objective and Risk in DLIB HOG-SVM detector

I am using dlib simple object detector for training a HOG-SVM object detector. Everything is working fine when I test manually. However, I can't find any resources that tell me what is the meaning of ...
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10 views

Are image classification nets independent of input size ? Which ones?

Most models I have seen have a dense layer at the exit of the network with a softmax function or a relu sometimes, so I thought this was confusing: The major hurdle for going from image ...
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16 views

Recognize Logos and their Sources

I am working on a problem where I have to recognize logos and also output about the logo placement (logo source). I have attached an image below for visuals, if any of the logos on the below image is ...
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1 answer
140 views

Can DeepSort be made to track objects beside people?

As far as my understanding goes, the model used for feature extraction in DeepSort is specified as the first argument of the function create_box_encoder in the file ...
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1 answer
474 views

Is it effective to use images without objects in object detection?

I am currently using faster_rcnn to train a set of images with only one category, in fact, there are only good images and images with defect in the whole dataset,and I use roboflow to labeling this ...
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36 views

What computer vision techniques can help me select the best image for object detection inference?

I have a lot of duplicate images. I need to make a selection to reduce the amount of images the Mask RCNN model will perform inference on. In every collection of duplicates, the images slightly differ....
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1 answer
163 views

What is 3D face recognition? and how we can check liveness of a face image?

Actually what is mean by 3D face recognition? In normal cases we are extracting face encoding s from a 2D image,right? Is 3D face recognition is used for liveness detection? how its possible?
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95 views

Image Alignment/Homography of Subject in Bounding Box

I've been trying to design an algorithm for aligning an object across two photos in realtime. I am able to localize the object (create an ROI/BBox) through an object detection (siamese) network for ...
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591 views

Object detection: when there's only 1 object in each image

Good day. I have a custom dataset for object detection, which has imbalance that each image has only one object annotation. I trained the object detection model(Efficientdet-dx) on TensorFlow object ...

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