Questions tagged [object-detection]

Object detection is a computer-vision and image-processing technique for locating instances of objects in images or videos. Common applications include face detection and object tracking. Object detection algorithms typically leverage machine learning or deep learning to produce meaningful results.

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object detection neural network's bounding box error converging instantly during training

I tried to make an SSD neural network for object detection. For now, i'm using 600 (700x700) training examples, i'm planning of using 1000 (I only have one class) or more if needed. However, there ...
KarimCool's user avatar
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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 ...
Mehdi Charife's user avatar
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Where exactly in YOLO's architecture is the input image divided into a grid?

I am currently studying the YOLO algorithm for a project. What I'm not quite sure about is where exactly the input image is divided in an SxS grid. After my research on the paper, videos and websites ...
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Best practice labeling grouped anomalies for object detection

I would like to train object detection model (e.g. YOLO) for images that contain anomalies. The anomalies are essentially the holes in a surface of different sizes. How do I label correctly such ...
In777's user avatar
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Model.train( ) returns automatically in YOLO v8

I'm trying to find the best sets of hyperparameters for my YOLO V8 model on my custom dataset with RayTune. I wanted to train the model with model.train() and return some of the evaluation metrics, ...
abdus samad's user avatar
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How does the background class work in object detection?

I am using YOLOv5 for object detection. I understand that any labelled classes that are not predicted, that is, false negatives (FN) shows up as background. But how are the false positive (FP) being ...
Icecream Pudding's user avatar
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Detecting scratches in car surface, may be data drift

I am trying to detect scratches on the car surface using Yolo, I have training images like the one below, and I am getting good mAP (around 0.83) on the validation and test dataset. The training image ...
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YOLO v5 labelling dilemma

let's say I want to detect 3 different types of objects in an image using transfer learning from YOLO v5. I have only 1 custom input image, with over 2000 labels comprising of all these 3 unique ...
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Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model

At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be this exact same model as the ...
Serilena's user avatar
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How do you find the coordinates of the bounding box for meituan Yolov6?

I'm trying to track a runner in a frame and eventually output velocity of the runner. The way that I am trying to do this is by finding the midpoint of the bounding box and then calculate the change ...
Aidan K's user avatar
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How to label images with no object of interest for an object dection project?

I have an object detection project of two classes (person, animal), and I want to use darknet/yolov4 for it. The images can contain person(s) and/or animal(s), or none of these classes. For example, ...
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How to associate each object in the prediction to its annotated version in YOLOv5?

Imagine we have one image from the COCO validation dataset. This image has 7 annotated objects: knife, carrot, person, table, chair, apple, and orange. When I feed it to YOLOv5, the predictions are ...
Hamzah's user avatar
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Can we create tensorflow or tflite model for object detection without uploading our dataset images to cloud?

I need to create a custom Tensor flow lite model for object detection to integrate in an android app. But I have a constraint that the dataset images to be used is confidential and cant be uploaded ...
Roohi Zuwairiyah's user avatar
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Object detection using EfficientDet

Unfortunately I don't have a specific question because I just started looking into this hours ago but I am trying to write a script that will use EfficientDet to detect object in some images acquired ...
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How can I separate and follow the plants that are very similar to each other with the YOLOv5 algorithm?

I want to differentiate between fern and mint using the YOLOv5 algorithm. Now I can take pictures of fern and mint, mark them on LabelImg, and train them in collaboration with Google. However, since ...
Özgür Önder's user avatar
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research papers on mean average precision

I've been coding YOLOv1 from scratch, are there any good papers which explain and/or give code (or pseudocode) for mean average precision? I searched but couldn't find good ones
vivian.ai's user avatar
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Faster R-CNN: are the proposal coordinates predicted in stage 1 fed as input to the bbox regressor of stage 2?

If I understand correctly, stage 2 of Faster R-CNN "refines" the proposals predicted by stage 1. However, this would require providing the coordinates from stage 1 as input to the bbox ...
Pablo Messina's user avatar
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Object Detection: Setting threshold values as trainable parameters?

I am building my first object detection model (Mobilenet SSD, to detect animals in images) and happy with the current test results. When I tested it using images without bounding boxes, I noticed some ...
user27771's user avatar
5 votes
3 answers
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Spatial Join Pandas Dataframes of Bounding Boxes (cross match)

Problem Statement Imagine there are two almost identical images with annotations (bounding boxes for certain objects), where one is so-called golden image (template) containing all must-have objects (...
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Yolov8 - box_loss and dfl_loss stays at 0. cls_loss converges. Model not giving me bounding box predictions

I'm having trouble using Yolov8 to work properly. I have my own custom dataset and an online dataset that I am using. Yolov8 trains on these datasets. However, the only metric that converges is the ...
Veggeata's user avatar
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Memory usage of a DNN model during inferencing

I am running a DNN model (YOLOv7) on GPU to detect objects in a video stream. The memory usage on my task manager shows that I am using up to 2GB of my RAM! The GPU Ram usage is almost 1 GB. I am ...
Hossein's user avatar
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Training an Object Detection Model from scratch vs. pretrained weights

I have a question related to training a object detection model: Lets say I have trained a model for detecting 1 class with, say, 500 images including positive and negative samples and saved the best ...
Uce's user avatar
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multi label classifictaion - single class or group labels?

I currently working on a vehicle dataset, with the goal of detection and classification vehicle types (car, bus, truck, motorcycle). In addition, for each vehicle, I want to detect and classify each ...
Eviatar Ben-Arush's user avatar
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Object detection (with bounding boxes) end-to-end as an auxiliary task (as in multitask learning)?

Let's say that I have a visual encoder (CNN or ViT) which outputs a volume of local features of dimensions WxHxD plus a global feature vector of dimension D, which I'm currently using as the backbone ...
Pablo Messina's user avatar
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How to annotate a custom dataset to run Yolov7?

I have a personal dataset of mine on which I want to use the yolov7 network (pytorch). How do I manually annotate the dataset (assuming I know which part of the images I know to annotate) to train the ...
Academic's user avatar
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How to process batch of images for video, using Object Detection Api?

Neural Networks are capable of processing batch of images at once. I am trying to implement this in my object detection api code but I couldn't do it. This is where I take video reader's each frame ...
Murat Şahin's user avatar
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How to create a synthetic dataset for object detection with GTA-V

I am planning to do a project of object detection in the off-road environment. There is not much labeled data available for this. I was thinking about creating my own dataset with GTA-V but I don't ...
programmer_04_03's user avatar
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2 answers
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how to lower false positive ratio on object detection using negative examples

There is a similar question here but the answer is not so clear; Basically, I have a model that detects only and only "matchbox". However, it has a high false positive ratio specially ...
user702846's user avatar
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what labeling format has negative Bbox values in labels?

I have a labeled dataset for object detection few thousands of images with annotation on csv file the csv contains these columns image_path, class, xmax, xmin, ymax, ymin looks like Pascal voc format ...
Mustafa Azzurri's user avatar
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YOLO : why does changing the confidence threshold change the mAP@0.5?

I trained a YOLOv7 model for a detection task. I have only one class, which is the object I want to detect. I ran test.py with --conf-thresh to 0.001 (default) and a second time with --conf-thresh to ...
Quintino's user avatar
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Finetune an already finetuned transformer model

I have a use case for a model where the backbone is a transformer(ViT-based) and has been pretrained for Masked Image Modeling. The output of the backbone is pushed into an FPN tensor which then Mask ...
Carl Rynegardh's user avatar
1 vote
1 answer
539 views

What is the architecture of ssd_mobilenet_v2_fpnlite_640x640?

What is the architecture of ssd_mobilenet_v2_fpnlite_640x640, which is a model available on TensorFlow model zoo. If my understanding is correct, mobilenet is used for feature extraction , while SSD ...
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Does decreasing the 'tflite_max_detections' variable in TFLite have any positive effect?

I'm currently training my own object detection TFLite model using the TFLite model maker. Theres a variable you can set called 'tflite_max_detections', which is by default set to 25. Does anyone know ...
Gereon99's user avatar
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123 views

Split dataset into Train/Validation/Test for Object Detection

I have a dataset for Object Detection with YOLO format labels, each imagine can have occurences of different classes and multiple occurences of the same class. How can the dataset be divided into ...
1stTimeStackOverflow's user avatar
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Document Layout Detection - input layout fixing

I am performing documents layout detection. Model predicts tags/labels and groups them, so final output is some kind of tree. Of course I have annotated gold layouts (trees). The main difference from ...
Dawid's user avatar
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What are the limitations of YOLOv7?

I'm doing a survey on YOLO versions and couldn't find any document that mentions limitations of YOLOv7 (You Only Look Once). Can someone please provide useful links to refer? So far I only found that ...
Intern's user avatar
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How to use Image Annotation for Image Classification?

I have been working on Crop disease identification, but with the given data i failed to get the desired accuracy using random forest classifier. I was suggested to use image annotation and I did using ...
M Bilal Ayaz's user avatar
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Image registration of detected objects across frames

I have a set of images on which I do object detection. The images are of irregular shaped entities (non-convex shapes), within which we detect artifacts. These artifacts are are detected as bounding ...
Gaurang K's user avatar
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327 views

What can I do when my object detection model learns background images instead the objects?

I'm training a machine learning model using YOLOv5 from Ultralytics (arch: YOLOv5s6). The task is to detect and identify laundry symbols. For that, I've scraped and labeled 600 images from Google. ...
Joba's user avatar
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How many bounding boxes does the YOLOv6 model predict in total before thresholding?

I understand that the YOLOv5 model predicts 25200 bounding boxes between all 3 levels of output. How many does the YOLOv6 model predict, if the input resolution is 640x640?
Fijoy Vadakkumpadan's user avatar
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How many bounding boxes per grid cell does the YOLOv4 model predict in the original paper?

Reading through the original YOLOv4 paper, I can't tell how many bounding boxes are predicted per grid cell (before any thresholding). I understand that YOLOv4 uses the same head as YOLOv3, so is it 3 ...
Fijoy Vadakkumpadan's user avatar
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How to identify outlier images within a set of similar images when no external classification data is available?

I'm trying to automate outlier detection in Python for a computer vision project I'm working on in which many instances of similar objects will be in view of the frame, and I want to verify that all ...
harke's user avatar
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What kind of object detection model is required?

I have some images, and my task is to build an object detection model for detecting tables and equipment photos in the image. The target would be detecting objects (table and equipment), so I can crop ...
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what is the difference between 'object detection' and 'outlier detection' in computer vision?

If I'm looking at drone footage, and I'm looking for tennis courts, then I'm doing object detection. If I decide that a tennis court is an 'outlier' as opposed to the rest of the landscape, am I now ...
tumultous_rooster's user avatar
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Should training images contains single or multiple object instances?

I'm pretty new to ML so I apologize for the potentially trivial question; I've been unable to find a clear answer to my question. Let's imagine that I want to build a model that is able to detect ...
pookie's user avatar
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Given an image how to find height of an object?

If I have an image of apple then how can I find the height of an apple using Deep learning? The photo of an apple is taken from the top view and I want to detect the height of that apple. How to do it?...
vivek Chaurasia's user avatar
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597 views

Which deep learning model is best in terms of instance segmentation and Object detection both?

I am trying to find most efficient and robust Object detector+Segmentation model. I came to know about Mask-rcnn, Yolov5, Yolact, yolov7. As, YOlov7 is new and i read somewhere that yolov7 surpasses ...
Hamza's user avatar
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Pros and Cons of Object Detection vs Instance Segmentation?

I know what the difference is between object detection and instance segmentation (i.e. both detect individual objects and label them but one is via bounding boxes versus one is pixel-wise), however I ...
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How to mark right path in the image of an intersection based on the detected traffic sign using deep ensemble learning, stacking approach?

I have a very complex problem and I do not know which approach could be useful for this. I have the images of the intersections, roads and these do not have traffic lights and we can drive only in one ...
Koko's user avatar
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Recognize chatbox on game screenshots

I have videos from a computer game. In this computer game, during the rounds, there is a chat box where players can write messages. I want to read the content of this chatbox. Difficulties are here: ...
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