Skip to main content
Share Your Experience: Take the 2024 Developer Survey

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.

Filter by
Sorted by
Tagged with
0 votes
0 answers
6 views

ways to calculate the accuracy of a object detection model

In case of classification, we will calculate the accuracy by performance of model on test dataset. ...
MohanGandhi's user avatar
2 votes
1 answer
26 views

How to chose the right activation function for CNN output depending on the output value ranges?

I'm working on training a CNN model that takes an eye image as input and outputs the 5 coordinates of the ellipse representing the pupil ...
Ersven's user avatar
  • 23
0 votes
0 answers
19 views

Convolutional Filters that detect number of ones in binary matrix

I am studying a deep learning course and one of the questions in the course is like a puzzle game: Part (a) Given a 4 by 4 binary matrix (consisting only zeros and ones), design a CNN that can detect ...
Dan Lee's user avatar
0 votes
0 answers
12 views

Can a multi-task model work on conditions for each layer?

I am currently working on a multi-task model that needs to handle car detection, damage segmentation and license plate ocr. my idea was to only run the OCR layer when there is a license plate detected ...
Enes Aygun's user avatar
0 votes
0 answers
19 views

One shot object detection

I want to detect objects from a video. I can only have one example image and based on this, I want to detect whether this image is present in the video or not. What could be the best-suited approach?
Rajeev Radhakrishnan's user avatar
0 votes
1 answer
27 views

How to interpret annotation data?

I am new to datasets. I have got an annotations train.json for MR image data like this - I want to train a Yolo-V8 model using this MR data images extracted from dicom raw data and annotations for ...
mrin9san's user avatar
  • 168
1 vote
0 answers
20 views

Improving Detection Model - Adding image clarification

I trained an object detection model with 5K images, it works most of the time, but I am facing an issue, for few times, the object is not getting detected. So, I planned to retrain the model, for that ...
Vishak Raj's user avatar
0 votes
0 answers
5 views

CNN to estimate a density map of an image, used to predict the object count

I'm trying to count the number of objects (larvae in this case), from a video. The constraint is, I cannot use any ML model, nor can I train my dataset as there are no annotations available. This ...
driver's user avatar
  • 101
0 votes
0 answers
9 views

Why do object detection model adversarial masks look different from those of image classifiers?

I was messing around to observe the behavior for adversarial attacks on image classifiers, and decided to try it with an object detector as well. I realize that inference time attacks are more complex ...
Soumil Datta's user avatar
0 votes
0 answers
3 views

How to use anchor box priors in yolov2?

I saw the paper in yolov2 where they said they picked some anchor boxes to start with. But the output also predicts a the position, width and height of the box. So there's no way to make the neural ...
IKnowHowBitcoinWorks's user avatar
1 vote
2 answers
31 views

Image segmentations vs image detection

If I need to detect on an image some objects and we are only interested in counting them, between image segmentation and object detection which one would you think would yield best results in terms of ...
Dinu Mihai's user avatar
0 votes
0 answers
25 views

Tile color, shape, and type detection altogether

I'm trying to apply some detections/classification on the set of tiles we have. Specifically, I need to detect color (15 classes), pattern (25 classes- on the surface of tiles, there can be certain ...
Mary's user avatar
  • 217
0 votes
0 answers
21 views

How to treat "ignore" boxes during object detector evaluation?

I want to evaluate the performance of multiple object detectors for comparison, each of them has been trained on this data. This dataset has images labeled, where each image can have multiple labels. ...
hafiz031's user avatar
  • 121
1 vote
1 answer
74 views

Why not using segmentation architectures for object detection?

Current object detection architectures like Faster-RCNN and YOLO seem to be overcomplicated in comparsion with segmentation architectures like Unet. So, why can't we just draw some rectangles around ...
Eugene's user avatar
  • 13
0 votes
1 answer
53 views

Optimizing YOLO for Diverse Takeaway Item Detection: Single vs Type-Based Classes

I'm using YOLO to detect various 'takeaway' items, currently all marked as class 0, which vary very widely(like groceries) in shape and type. Considering the introduction of new items on which the ...
Mike Like's user avatar
0 votes
1 answer
404 views

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 ...
Mary's user avatar
  • 217
0 votes
0 answers
20 views

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
0 votes
0 answers
23 views

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....
Meeresgott's user avatar
1 vote
0 answers
204 views

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
0 votes
0 answers
12 views

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 ...
wll's user avatar
  • 1
0 votes
0 answers
77 views

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 ...
sagi's user avatar
  • 101
0 votes
1 answer
27 views

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
1 vote
0 answers
18 views

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
0 votes
1 answer
48 views

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: ...
th2797's user avatar
  • 23
0 votes
0 answers
24 views

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
0 votes
1 answer
84 views

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’...
Mary's user avatar
  • 217
0 votes
0 answers
68 views

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 ...
peter's user avatar
  • 105
1 vote
0 answers
70 views

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: ...
Emmanuel's user avatar
  • 111
0 votes
0 answers
90 views

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
  • 37
0 votes
0 answers
21 views

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
0 votes
0 answers
188 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 ...
Mehdi Charife's user avatar
1 vote
0 answers
171 views

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 ...
Jannes's user avatar
  • 11
0 votes
1 answer
29 views

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
  • 3
0 votes
0 answers
1k views

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
1 vote
0 answers
17 views

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 Al-Qadasi's user avatar
1 vote
1 answer
47 views

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
0 votes
1 answer
50 views

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
1 vote
1 answer
458 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
357 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 (...
TwinPenguins's user avatar
  • 4,279
0 votes
1 answer
2k views

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
1 vote
0 answers
139 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
  • 11
0 votes
2 answers
63 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
103 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
341 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
1 vote
1 answer
2k 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
  • 13
0 votes
3 answers
166 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
0 votes
1 answer
243 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
0 votes
1 answer
1k 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
  • 123
0 votes
1 answer
211 views

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
1 vote
0 answers
19 views

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 ...
sksoumik's user avatar
  • 111

1
2 3 4 5
7