Questions tagged [yolo]

"You Only Look Once", a Deep Learning-based object recognition algorithm available in several different software implementations.

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Why regarding mean Average Precision for 50 and for 50 to 95? And can you average different evaluations?

I saw a lot of papers using mAP@50 and mAP0:5:95, but in terms of deciding how precise a trained object detection model is, I do not understand why often both values are discussed and shown. Wouldn't ...
Taka Incur's user avatar
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How is the backbone and head of YOLOv8 connected?

I have view this . But C2f only has single output tensor. What is the meaning of the connection between Backbone and Head in the diagram? Is it a copy of output ...
Audra Jacot's user avatar
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Questions on filtering out predicted boxes during training for YOLO family of algorithms

Does any of the YOLO models use NMS during training? From going through the papers they only explicitly state that NMS is only applied during inference, unlike Faster-RCNN. Does any YOLO (or other ...
Yandle's user avatar
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YOLO v1 - range of bounding box prediction value x,y,w,h

Question YOLO v1 paper section 2 Training says the bounding box prediction from the model is normalized between 0 and 1. Is this actually true if the entire input image is a part of a larger object? ...
mon's user avatar
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Yolo v1 - what is the purpose of the confidence Ci?

YOLO v1 model predicts the confidence score $\hat{C_i}$ but I am not clear with the purpose of $\hat{C_i}$. Definition of the confidence score in the YOLO v1 paper. $\hat{C_i}$ is used in the loss ...
mon's user avatar
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Average Precision (AP) for object detection, huge confusion

I've been reading about how object detection models are evaluated. It seems that the metric most often used is AP. But I have stumbled upon 2 different approaches that I think mean completely ...
Tomé Silva's user avatar
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YOLOv1 and YOLOv2 -- Pr(Object) and "responsible" boxes

In the YOLOv1 paper, Pr(Object) denotes the probability that there is an object in a certain grid cell. When it comes to the ground truth values, which values can Pr(Object) take? Only 0 and 1? What ...
keezar's user avatar
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Can we combine different yolov5 models trained of different classes into one?

Suppose I've a yolov5 model trained on cars and second trained on bus and third trained on bike and so on. Is there a way through which I can combine all the model into a single model? As by running ...
Janardan Pandey's user avatar
4 votes
1 answer
884 views

Training with extremely imbalanced Dataset

I have a object detection problem which has extremely imbalanced dataset. Lets say there is only one class to detect, say banana or not banana. This detection network will be used in a real case where ...
Uce's user avatar
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I am trying to do object detection using Yolov5 and modify the model. How can I do that?

I want to modify Yolov5 and see how it performs. Here's the yaml file https://github.com/ultralytics/yolov5/blob/master/models/yolov5s.yaml How do the make the changes in the yaml file if I want to ...
Lucie's user avatar
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Yolov3 targets build, Do all 3 scales need to have an anchor box designed for each object in the image or just the scale with better IoU? [closed]

I'm implementing Yolo v3 in Pytorch, Imagine we have an image with a large object in it, whem building targets, I'll have to assign the anchor box with highest IoU with this object for each scale, (So ...
Vinc's user avatar
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YOLO v2 loss function

I'm trying to understand (and implement) the YOLOv2 loss function, which is not given explicitly in the original paper. There are several posts on this topic, but quite a few seem to confuse the ...
eike's user avatar
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Math behind predicting the dimensions of bounding boxes

I have been trying to understand the mechanics behind YOLO v3. I got stuck at the section which defines the calculation of bounding box. Going through various blogs, I found that The dimensions of ...
Rajat's user avatar
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Questions about mAP results from YOLOv2 paper

In the YOLOv2 paper, is the mAP metric displayed in Table 3 calculated in the same way as the metric in the column '0.5' from Table 5?
Yandle's user avatar
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How are the confidence scores in YOLO computed?

I have read Yolo Loss function explanation but none of the answers discuss how box confidence scores are computed. The YOLO paper uses the following loss function: I'm confused about how confidence ...
Yandle's user avatar
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Question about center coordinate definition in region proposal networks

In the YOLOv2 paper, page 3, it states that region proposal networks predicts $t_x$ and $t_y$ where $(x,y)$ center coordinates are calculated as: $$x=t_x*w_a-x_a$$ $$y=t_y*h_a-y_a$$ such that for $t_x ...
Yandle's user avatar
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3 votes
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Question YOLOv2 bounding box prior

In the YOLO9000 paper, they define the distance between a box and centroid as $d(box, centroid) = 1 - IOU(box, centroid)$. I think box here is a ground truth bounding box, but what is centroid?
Yandle's user avatar
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Conditional class probabilities in YOLOv1

In YOLO v1, authors defines conditional class probabilities (P(Class_i/Object)) I don't understand that authors can define the head output to conditional class probabilities. When the model finishes ...
Jaehong choi's user avatar
1 vote
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how to check if unknown object partly covers the object i want to detect

I want to detect an object from an image,I use yolo object detection. I detect car from the image. I consider the case when another unknown object partly covers it, how can my program know that there ...
anahit hambardzumyan's user avatar
2 votes
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319 views

In YOLO, can there be more than one class within a cell?

I'm confused by the fact that YOLO** can have multiple bounding boxes per cell, but there is only one class vector. Does YOLO allow the truth/training to have more than one object in a cell, each with ...
Mastiff's user avatar
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1 answer
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Performing object detection without localization

I'm looking to build a computer vision model that can detect the presence or absence of several classes of object within an image, but the localization of these objects is not required. The end ...
Joe Kerrigan's user avatar
1 vote
1 answer
302 views

What is the difference between these error metrics in object detection

I am wondering what is the difference in these error metrics (and what they are) in object detection: mAP_0.5:0.95, mAP_0.5, recall, precision
Peter's user avatar
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Does it help to provide training samples with no target objects in object detection?

I am training a Yolo for object detection. I was wondering if it will help to provide images with no instances of the target object present. If so, what would the VOC label of such an instance look ...
maininformer's user avatar
1 vote
1 answer
151 views

Does the Object you Want to Classify have to be in a Cluttered Background in Yolo?

I'm trying to classify plant diseases with the plant village dataset, shown in the image above. These images are all very consistent, with exactly one leaf and similar backgrounds. However, I am ...
ddd's user avatar
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YoloV3: Training set, true label boxes vs anchor boxes

I understand the anchor boxes as a set of boxes that based on a comprehensive exploration of the data ( all the true bonding boxes) best describe the variable sizes of all true boxes in the training ...
user317766's user avatar
1 vote
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670 views

How to add labels to an already trained Yolo model?

I'm learning ML and I'm exploring object detection and classification. I discovered Yolo few months ago and it's impressively efficient and accurate. There are several pre-trained Yolo models on the ...
Spiralwise's user avatar
3 votes
1 answer
2k views

What are "Grids" and Detection at different scales" in YOLOV3?

I've recently started working with Yolov3 and the more I go in depth, the more confused I get. In the simplest terms what I think about YOLOV3 ...
Deshwal's user avatar
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Darknet and Data Augmentation

In the darknet deep learning framework .cfg files we see parameters like angle, saturation, exposure These parameters are used ...
pentanol's user avatar
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Why use multiple anchor boxes with the same positions in a multi-box detector?

What is the benefit of using multiple anchor boxes with the same positions in a single-shot multi-box detector model, like YOLO? In particular, I notice Google's BlazeFace model does this. If the ...
algal's user avatar
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Why Anchor Boxes in Object Detection

What I understand from the anchor boxes is that they are predefined set of boxes of different sizes and shapes. A model like YOLO predicts offsets of the coordinates for each anchor box along with ...
azhar baloch's user avatar
5 votes
1 answer
3k views

1 neuron BCE loss VS 2 neurons CE loss

I built a custom version of YOLO that should only detect one type of objects, where the objectness measure (which tells how likely a bounding-box contains an object of any type), is learned using a ...
SomethingSomething's user avatar
1 vote
0 answers
179 views

yolo v1: how gradients in grids with no objects overpower

I am reading yolo v1 paper. I am having confusion while trying to understand this: "Also, in every image many grid cells do not contain any object. This pushes the “confidence” scores of those ...
Leo's user avatar
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yolo v1: why we weigh localization error more than classification error

I'm reading yolo v1 paper. I am trying to understand this part of the paper: "We use sum-squared error because it is easy to optimize, however it does not perfectly align with our goal of ...
Leo's user avatar
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384 views

In the case of YOLO, how does the network assign a box in it's grid based on the midpoint of the object?

My question is that how in YOLO, the networks does the midpoint of grid cell think ? I'm not completely sure I understand it. How can we know the midpoint of any object before actually knowing where ...
PseudoCodeNerd's user avatar
1 vote
0 answers
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Best way for robust hand tracking on PI 4

I need a robust hand tracking which should be running on a Raspberry Pi 4 model. Does anyone have some experience with that? One way could be to use OpenCV but I think it's just using the skin color ...
kai müller's user avatar
3 votes
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1k views

Yolov3: Single-class vs multiple class

I'm really new to object detection with Yolov3. Let's say I have 10 classes and the amount of data is approximately the same. Do I achieve better average precision when I use 10 Yolo models and train ...
kai Herbst's user avatar
2 votes
1 answer
81 views

Performance of MaskRCNN/YOLO as a function of object size in pixels

I am trying to find references on how the resolution of an object affects the ability of object detection systems such as MaskRCNN and YOLO to correctly identify the object. For example, if the ...
Surgical Commander's user avatar
2 votes
1 answer
730 views

How exactly the midpoint of the object is selected in YOLO algorithm?

The boundaries of the object are encoded into 4 scalars: Bx, By, Bh, Bw. Bh and Bw are calculated using the ratio of the width of the bounding box to the width of the relative grid cell. But I can't ...
roman_ds's user avatar
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4 votes
2 answers
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How are YOLO anchor boxes generated?

I am recently trying out darkflow, a Tensorflow implementation of Darknet written by Joseph Redmon. Looking at the configuration files, I noticed a section called region as shown below. ...
user3600725's user avatar
2 votes
0 answers
934 views

The reason for multiple bounding boxes use for each grid cell - YOLO

I'm not quite sure what is the main reason why YOLO uses multiple bounding boxes for a grid cell. An answer I can find on web is for multiple aspect ratio in the prediction. However I don’t think it’s ...
StapleStable's user avatar
5 votes
2 answers
2k views

What is sigma function in the YOLO object detector?

I have gone through the YOLO9000 paper, in that they have mentioned that network predicts 5 coordinates of the bounding box, and from that we find the exact centre coordinates and the width and height....
bibinwilson's user avatar
1 vote
1 answer
770 views

Combining custom YOLO network for face detection with another CNN

I am looking for a way to build and train an end-to-end CNN that contains two steps: 1) a CNN for finding a face and hands in the image and 2) CNN that works on the crops of the face and hands. To ...
Paul Beloff's user avatar
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1 answer
294 views

How to "use" Yolo Loss Function

I am dealing with Yolo Loss Function (the following). $$\begin{align} &\lambda_{coord} \sum_{i=0}^{S^2}\sum_{j=0}^B \mathbb{1}_{ij}^{obj}[(x_i-\hat{x}_i)^2 + (y_i-\hat{y}_i)^2 ] \\&+ \lambda_{...
aleio1's user avatar
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2 votes
1 answer
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YOLOv3 loss function

Follow-up to stats.stackexchange.com/questions/373266/yolo-v3-loss-function: In trying to finalize the development of my training labels and loss function I'm confused by the part in bold in the ...
luis-gonzales's user avatar
1 vote
1 answer
2k views

what purpose do the grid cells serve in YOLO object detection algorithm?

so I was looking at YOLO and I read several blogs online, but one concept I'm having trouble understanding is why do we want to divide the image into different grids, and then predict the bounding box ...
ai_boy's user avatar
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1 vote
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434 views

Is YOLO a good algorithm for defect detection on images?

I wish to train an algorithm to detect defects on images of labels. These may be such things as scratches, tears and voids. I would like to try to train a YOLO algorithm to do this, but it is very ...
Sotades's user avatar
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13 votes
1 answer
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Yolo v3 loss function

The original loss function can be seen here and is more or less explained in Yolo Loss function explanation: \begin{align} &\lambda_{coord} \sum_{i=0}^{S^2}\sum_{j=0}^B \mathbb{1}_{ij}^{obj}[(x_i-...
sachinruk's user avatar
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11 votes
1 answer
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On Yolo, and its loss function

I'm having a hard time understanding some on the inner-working of YOLO, especially the loss function depicted in this seminal paper. Bear in mind that I'm nowhere closed to being a specialist in deep ...
Hermès's user avatar
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5 votes
1 answer
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What is the need of multiple Bounding Boxes per grid cell in YOLO v1?

This question is regarding YOLO v1 architecture as in here. I am confused as to why authors have used 2 bounding boxes per grid cell for training. Assuming there can be only one object per grid cell. ...
Fenil's user avatar
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2 votes
1 answer
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Understanding the YOLO algorithm

I am trying to understand the logic behind object detection and the YOLO algorithm. I have read numerous blogs, tutorials, videos, papers, yet I am still not sure if I understood it correctly. Let's ...
Darlyn's user avatar
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