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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Car Make and Model detection

I am trying to develop a deep learning model that given an image of a car, it detects a car's make and model among 50 different brands, each with say another 50 models. What approach is probably the ...
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Tensorflow outputs nan for basic object detection/classification

I am receiving nan as my accuracy and loss outputs after each epoch for basic object detection in tensorflow. Also, my results (classification and bounding box ...
Clouseau's user avatar
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IoU when labels are different

The IoU focuses only on the bounding boxes. My predictions for one Image are (Yolo) e.g. label x y w h 0 0.1 0.2 0.3 0.3 1 0.9 0.9 0.05 0.05 And my ground truth is: label x y w h 1 0.1 0.2 0.3 0....
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Accuracy difference between 1-channel grayscale and 3-channel grayscale detection model

I have found no similar questions to this online, or answers for that matter. I am using cameras that output a grayscale image, which I feed into a Yolov8 object detection model (Specifically yolov8m-...
Alec van der Linden's user avatar
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Identify multiple people in images and count the frequency

I have multiple images posted by a user and I am interested to know how many times each unique person appears in the user's photos. For instance, the user might post photos of himself/herself with ...
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Torchvision Faster-RCNN, modified loss function

I'm trying to solve a problem of table detection in spreadsheets in Excels. I've came across this paper, which suggests to use modified version of Faster RCNN to do object detection on the ...
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Detector vs Classification - Detecting a netted bag for fruit/vegetables in image

The application is detecting the presence of a netted bag in an image. The image can contain fruit and vegetables, either with or without a netted bag around them, or below them (no constraints about ...
ADHD Productions's user avatar
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Can CNNs complete lines and contours?

Are there deep convolutional networks capable of recognizing two overlapping triangles in this image - or is this beyond the capabilities of CNNs? And are there CNNs that can recogize two boxes ...
Hans-Peter Stricker's user avatar
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MaskRCNN.train gives 'list index out of range'

I have been trying to use MaskRCNN with a Resnet backbone on the DeepFashion2 Dataset for instance segmentation. The custom configurations are as follows: ...
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How to train multiple inputs for my model?

I'm a high school student and a newbie in Machine Learning. I just learned Machine Learning Crash Course by Google so my knowledge's still limited. I'm trying to build an Object Detection by myself ...
Nguyễn Phúc Khang's user avatar
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Use computer vision to detect door blockage

I want to detect door blockage on a camera. Basically if the exit door is blocked by an object, it detects it as an anomaly. How can we do it? Is it possible to do it using OpenCV? Remember, it doesn’...
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How to get loss functions on evaluation part from the following training procedure?

So, I have followed this tutorial: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html#training-pipeline-conf and use it to make object detection. More specifically ...
just_learning's user avatar
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Annotating and Structuring a Dataset for Duplicate Detection

I'm currently working on a project that requires the detection of duplicate bands in Western blot images. The task involves two types of duplicates: ...
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Object detection on largest number of classes

Does anyone know any pretrained object detection models to run with python with highest number of objects to be recognised? Yolo finds 80 objects, it is good if I can find a larger number. It would be ...
Jean's user avatar
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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 ...
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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, ...
David293836's user avatar
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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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103 views

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
294 views

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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124 views

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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41 views

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.sahin.dev's user avatar
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36 views

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
53 views

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
1 vote
1 answer
58 views

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 Alahmid's user avatar
1 vote
1 answer
247 views

YOLO : why does changing the confidence threshold change the [email protected]?

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
1k 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 ...
gkl kmr's user avatar
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3 answers
140 views

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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1 answer
196 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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972 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?
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