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Questions tagged [yolo]

For questions related to the family of models known as YOLO (which stands for "You Only Look Once"), which were proposed by Joseph Redmon et al. There are at least three YOLO models (versions 1, 2, and 3).

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How to recognize the state of a basketball player (using Yolov5)? [closed]

I am new to AI. I am wondering if it is possible to build a system that can tell the state of a basketball player. For example, the system should be able to tell the player is dribbling, shooting or ...
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15 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 "...
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1 answer
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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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1 answer
23 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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Which is the best model for counting how many people are in an inside car image?

I'm new on AI... I've been given a mission of finding a model which detects how many people there are on a inside car/truck image. So far I worked only with YOLOv4 with OpenCV using yolov4 weights. ...
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Should we collect additional images if we use pre-trained dataset for specific classes?

At the moment, I'm working on one a project related to object detection. I'm going to use YOLO because it is a better option. I have collected images for traffic signs, but I also need to detect cars, ...
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Yolo objectness parameter (called p0) vs probability parameters as explained by Joseph Redmon

I have been watching Joseph Redmon (developer of YOLOv3) lecture about YOLO from 45:04 where he explains why he needs both predictions: "objectness" called P0 VS class probabilities called ...
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1 answer
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YOLO - are the anchor boxes used only in training?

another question in YOLO. I've red about how YOLO adjusts anchor boxes by offsets to create the final bounding boxes. What I do not understand, is when YOLO does it. Is it being done only during the ...
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YOLO - does the Intersection over Union is actually a part of Non Maximum Suppresion

In the Stack Overflow thread Intersection Over Union (IOU) ground truth in YOLO they say that in YOLO actually the IoU (intersection over union) is used twice: during training to compare ground truth ...
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  • 131
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Transfer learning on YOLOv5 for character and shape detection

The task is to detect rotated alphanumeric characters embedded on colored shapes. We will have an aerial view of the object (from a UAS: Unarmed Aerial System), something of this sort: (One Uppercase ...
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Are the output dimensions of the first and second convolutional layer in YOLO paper correct?

I was reading the last version of the YOLO paper available in Arxiv, and I don't fully understand the output dimensions (I understand width and height, but not depth) of the first and second ...
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Multiple labels for the same rectbox?

My goal is to identify the horse in a photo. I'm dealing with about 500 unique horses. My feeling is that the best way to distinguish one horse from another is by its face. So I trained Yolov5 ...
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1 vote
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Different equations for Yolov3 in courses/ articles and Darknet GitHub code?

I am confused by the equations for bounding boxes I find online. Some articles say that box_width = anchor_width * exp(residual_value_of_box_width)) and the ...
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1 vote
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In anchor based object detection, why don't the anchors share the same weights?

After reading about YOLO V3 and Faster R-CNN, I don't understand why the weights for the regression head aren't the same across all boxes of the same size. Given that the backbone of these systems is ...
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Is there anything wrong with this YOLO loss function?

I have implemented the YOLOv1 loss function as: ...
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What is meant by "training a YOLOv5 on custom dataset"?

I am new to AI/CV domain. I see a lot of tutorials on "training a YOLOv5 on custom dataset". As per my knowledge, Basically, YOLO is a giant neural network trained on a particular set of ...
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Should I label static objects on video dataset?

I'm using nvidia Transfer Learning Toolkit to detect cars in some video frames. I found some dataset (for example https://www.jpjodoin.com/urbantracker/dataset.html and https://www.kaggle.com/...
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How to get bounding box coordinates of all detected objects in yolov5 object detection?

While there is a similar question on stackoverflow, it pertains to yolov4 which, unlike yolov5, uses darknet. Yolov5 is far more intuitive to use than v4 and so a solution to this in v5 is desirable. ...
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How to work deeper with YOLO v4 scaled

I am pretty new in object detection. When I did some classification using TF with pretrained models I changed some last layers and choosed how many layers I want to train. I don't really get it with ...
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Object Detection: Can I modify this script to support larger images (Scaled YOLOv4)?

I am looking at training the Scaled YOLOv4 on TensorFlow 2.x, as can be found at this link. I plan to collect the imagery, annotate the objects within the image in VOC format, and then use these ...
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Preparing data set for the YOLO algorithm

Hi I am working on a project which requires the You Only Look Once algorithm in order to classify and localise objects within images. I have to prepare my dataset (which has 2 classes, and predicts 6 ...
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1 vote
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What are the main differences between YOLOv3 and RetinaNet object detection algorithms?

I am looking at a certain project that compares performance on a certain dataset for an object detection problem using YOLOv3 and RetinaNet (or the "SSD_ResNet50_FPN" from TF Model Zoo). ...
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How to treat (label and process) edge case inputs in machine learning?

In every computer vision project, I struggle with labeling guidelines for border cases. Benchmark datasets don't have this problem, because they are 'cleaned', but in real life unsure cases often ...
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How are Ground truth provided to each Pyramid map in RetinaNet or YOLOv3 Paper? How is the mapping of Feature Pyramids done to Ground Truth

SO the YOLO V3 and RetinaNet both uses the Feature pyramids which look something like this: (except b and e which have one ...
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Aggregating 2D object detections into 3D object detections

I have a data set of 3D images with some bounding box annotations. The images are too large to train something like YOLO 3D (would run out of memory), so I instead created slices of the 3D images with ...
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Is it possible to modify or replace the basic network of YOLO?

I have an idea to adapt YOLO algorithm to my application, the original YOLO algorithm is for image classifications, which have 24 convolutional layers with output class of 1000, is it possible to ...
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2 votes
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Do filters have as many layers as the depth of the input in CNNs? [duplicate]

Firstly as an example here is the architecture of YOLOv2 I am trying to understand the depth of an output of a convolutional layer. For example, the first convolutional layer has the shape 3x3x32. So ...
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4 votes
1 answer
170 views

What is a unified neural network model?

In many articles (for example, in the YOLO paper, this paper or this one), I see the term "unified" being used. I was wondering what the meaning of "unified" in this case is.
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Is it possible to improve the average precision of YOLO trained on Open Images Dataset by fine-tuning it with COCO?

I consider pre-training a YOLOv5 with Google Open Images Object Detection dataset. The dataset includes general domain categories with ~15 M box samples. After the pre-training is done, I will fine-...
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Object detection noise filtering

In my project, I am detecting only one class, which is "airplane", using yolov5. However, at some frames, the neural network labels some of the buildings as airplanes, which obviously are ...
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3 votes
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If random rotations are included in the data augmentation process, how are the new bounding boxes calculated?

When studying bounding box-based detectors, it's not clear to me if data augmentation includes adding random rotations. If random rotations are added, how is the new bounding box calculated?
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1 vote
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How is the shape of the anchor boxes predefined in YOLO algorithm?

I am not sure if I really understand how anchor boxes are defined. As far as I understand, in YOLO algorithm you define a set of "good" shapes (anchor boxes) that may contain the object you ...
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1 vote
2 answers
148 views

Get object's orientation or angle after object detection

I'm trying to get a detected car's orientation when object detection is applied. For instance, when we apply object detection on a car and get a bounding box, is there any ways or methods to calculate ...
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328 views

Feeding YOLOv4 image data into LSTM layer?

How would one extract the feature vector from a given input image using YOLOv4 and pass that data into an LSTM to generate captions for the image? I am trying to make an image captioning software in ...
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2 votes
1 answer
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How does YOLO handle non-class objects?

I have been reading more about computer vision and I'm bothered by YOLO and similar deep learning architectures. The thing I am confused about is how non-class image sections are dealt with. In ...
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1 vote
1 answer
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Object detection: combine many classes into one?

I am trying to train a model that detects logos in documents. Since I am not really interested in what kind of logo there is, but simply if there is a logo, does it make sense to combine all logos ...
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2 votes
1 answer
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Data scan not making sense for coco dataset

I am doing a simple scan to see how dataset size affects training. Basically, I took 10% of the coco dataset and trained a yolov3 net (from scratch) to just look for people. Then I took 20% of the ...
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Intuition behind single-shot object detection

Is there a good way to understand how single-shot object detection works? The most basic way to do detection is use a sliding-window detector and look at the output of the NN to detect if a class is ...
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1 vote
2 answers
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What are the reasons behind slow YOLO training?

I'm testing out YOLOv3 using the 'darknet' binary, and custom config. It trains rather slow. My testing out is only with 1 image, 1 class, and using YOLOv3-tiny instead of YOLOv3 full, but the ...
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YOLOv3 Model Structure: Why is filters = (classes + coords + 1) * num?

Here's a tutorial about doing custom training of YOLO (Darknet): https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2 The tutorial guides how to set values in ...
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3 votes
2 answers
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Calculation of FPS on object detection task

How to calculate mean speed in FPS for an object detection model like YOLOv3 or YOLOv3-Tiny? Different object detection models are often presented on charts like this: I am using the DarkNet ...
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2 votes
0 answers
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YOLO 9000 about Better Stronger

In this paper, YOLO has three features compared to YOLO v1. This question is about Better and Faster. In the Better section, there are many techniques such as Batch Norm, Anchor Box and so on. In the ...
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2 votes
0 answers
485 views

How can I train YOLO with the COCO dataset?

I am trying to implement the original YOLO architecture for object detection, but I am using the COCO dataset. However, I am a bit confused about the image sizes of COCO. The original YOLO was trained ...
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4 votes
0 answers
1k 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 ...
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3 votes
1 answer
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How can I incrementally train a Yolo model without catastrophic forgetting?

I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want ...
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2 votes
1 answer
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How to detect multiple playing cards of the same class with a neural network?

I want to train an AI to detect the class (i.e. suit and rank) of playing cards. Playing cards from different decks may use slightly different shapes or colors to represent these attributes, and I ...
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6 votes
2 answers
2k views

What's the role of bounding boxes in object detection?

I'm quite new to the field of computer vision and was wondering what are the purposes of having the boundary boxes in object detection. Obviously, it shows where the detected object is, and using a ...
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11 votes
3 answers
11k views

Is it difficult to learn the rotated bounding box for a (rotated) object?

I have checked out many methods and papers, like YOLO, SSD, etc., with good results in detecting a rectangular box around an object, However, I could not find any paper that shows a method that learns ...
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2 votes
2 answers
208 views

Would YOLO be able to detect objects in "different" positions?

I have the following question about You Only Look Once (YOLO) algorithm, for object detection. I have to develop a neural network to recognize web components in web applications - for example, login ...
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1 vote
1 answer
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How to label training data for YOLO

I am having a question on how to label training data for YOLO algorithm. Let's say that each label Y, we need to specify $[P_c, b_x, b_y, b_h, b_w]$, where $P_c$ is the indicator for presence (1=...
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