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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What kinds of changes can I attempt on my object detector .config file to improve the detection accuracy?

I have trained an object detection model with 2 classes, around 7500 images, and approx. 10,000 annotations per class. I was able to fine-tune Faster R-CNN with ResNet (V1) from the Tensorflow Object ...
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Few shot learning and object detector

I have a dataset with a lot of classes (~10000+) but few examples by classes (~15-). I want to classify these classes, but there are some specificities. My examples provide from a video stream. ...
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Why do CNN regression models fail to localise an object when the scale, aspect & image type has significant variance?

Background I'm wanting to understand how to build an object detection algorithm from scratch. My initial thoughts were that architectures like YOLO and Faster-RCNN would find any object given enough ...
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Why is VGG16 better for object localisation than MobileNet?

Prologue I have been trying to perform object localization to provide the [x1,y1,x2,y2] coordinates of objects in an image using Keras. I was stuck for ever because I was using MobileNetV2 as my ...
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Extract features using Bounding Box

I have a ground truth bounding box for a 3d object. I would like to extract useful features for the object. My goal is to concatenate these visual object features with language features (from the ...
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COVID-19 Rapid Test Result Image Detection

I fine-tuned an Inception V3 model provided in AWS SageMaker to detect COVID-19 Rapid Test Results (see the image below for an example). I provided about 20 pictures of negative and about 20 pictures ...
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Minibatch SGD performs better than Adam for Region proposal network training

I am using both minibatch SGD (with momentum) and Adam for training a region proposal network. The library used is KERAS. The batch size in both cases is 5 and initial learning rate is 0.01. The ...
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Forward height/width information into classification model?

Please forgive me if it's not the right StackExchange, but I didn't find any related to computer vision questions. Problem: I have a pipeline for object detection and classification where I first ...
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How to create COCO format data out of list of boxes

I have $N$ images. I have a script that extracts boundary boxes of an object that I am interested in. For each image, I may get $m$ boxes. There is only one item that I am interested in which is cat. ...
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'Collision' resolution for precision in object detection

For object detection we often use metrics based on precision/recall. My question is what is generally the process of matching the prediction and ground truth bound boxes, when there are multiple ...
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What does the Region Proposal Network output in Faster-RCNNs?

Does it output corrections and offsets to the anchor boxes(that were generated by using some specific aspect ratios and scales)? Also if this the answer is YES, Suppose I have 3 scales - [8,16,32] and ...
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how to make image classification model to detect object and track object in a video

i have built a disaster classification model . now i want to use this classification model to detect ex- cyclone in a video to draw bounding box around it and track the cyclone if possible.is it ...
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can i do object detection on pretrained classification model...?

so i built a natural disaster classification model using transfer learning Renet50(tensor flow) got 98% accuracy and now instead of just classifying natural disaster lets say a cyclone appeared in ...
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Compute IoU for each class in Mask R-cnn

I'm trying to compute the IoU, with the matterport Mask R-cnn implementation, for each class (13 in total) that i have in my dataset. For now i managed to compute the average IoU for all the classes ...
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How to extract undetected object class labels after extracting `y_pred` from `predictions. pth` inference file for Mask rcnn

I training maskrcnn on a custom dataset with two classes (1 and 2). After testing, I get some files segm.json, predictions.pth, <...
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Extracting features from bounding boxes of CornerNet

I am using the CornerNet model. I want to extract features from specific bounding boxes that have been detected. Unlike Faster RCNN,...
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Implementing class weighting in Faster RCNN

I have a dataset (around 45,000 screenshots) of UI elements (UI trees containing element types and bounding boxes) and associated screenshots: The dataset is highly imbalanced with the button element ...
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Understanding how anchors are created in a regional proposal network

I understand that in Faster R-CNN, the image is fed into a pre-trained CNN (such as VG16). So say I have a 37x50x512 feature map. Firstly, I assume that each feature map (37x50x1) is fed into the RPN? ...
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object detection model with few shot and active learning

This video https://youtu.be/60Sk-mq3Cr8, from 0 to 2:00 minutes, mentioned an object detection model that can train on 10 samples and improved over time, what kinds of the latest model out there that ...
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Why do images in Open CV template matching get matched to the templates more than once?

The following code reads the set of input tiff files under tiffile and template tiff files under files and performs template matching on them. After the image gets matched, opencv contour extracts the ...
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Detect Bias in YOLO format object detection dataset

I work on YOLO data annotation. I want to know how to detect bias in the data before training in this kind of datasets. What are the metrics and analysis methods needed to use to detect bias in ...
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Training a YOLO-style object detector

tl;dr I'm trying to train a small CNN (two conv layers and two connected layers) to find humans in the COCO dataset. Is my network big enough, and if so, roughly how many epochs of training will it ...
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Where can I find free multi-instance single-label datasets for object detection?

I'm trying to find free multi-instance single-label datasets for object detection online. By "multi-instance and single-label" I mean that each image contains only object belonging to one ...
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understanding pytorch pycoco tools object detection output

I am using pytorch vision library for object detection. I am using utilities provided for objection detection metrics. https://github.com/pytorch/vision. I am seeing following output ...
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Spatial positional encodings Vs Learned positional encodings(Object queries)

I have been trying to understand facebook's Detection transformer(DeTr) paper. Architecture Most of the explanation about the architecture is straightforward. I don't especially understand the ...
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How to make my Object Detector generalizable to unseen data

I am working on a Vehicle detector using semi-supervised data. I created the data by applying another very performant Object Detector (which is slow and I can't use it for real-time detection). I ...
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Determining direction from a series of bounding boxes

I have a sequence of bounding boxes for people moving in and out of a camera's view. I'd like to determine the direction each person is moving (basically just left/right), so I can apply this as a ...
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Best way to train yolov5 on a custom dataset

I have a dataset with about 100 images that look like this. My goal is get yolov5 to detect buildings in similar images. In order to do this I would like yolov5 to get to close to 1 in precision on ...
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How to feed high resolution images to the model?

I want to do object detection , normally we have a size of image 256 x 256 or 128 x 128 but what if we want to feed high ...
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How to improve the performance of an object detector model?

I have few questions regarding improving the performance of my object detection model. When there is color match between person uniform and the background, it becomes difficult for my model to ...
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How to send frames of a video from a mobile application to an endpoint for object detection?

So usually in this case for object detection on video data I would load the model on the mobile application and then perform inference on it from there, but I have a scenario where it would be better ...
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yolo v4 vs yolo v4-tiny which is better for real time object detection or is that any that is better for real time object detection?

When I am comparing Yolo v4 and Yolo v4 tiny, I notice that the tiny one does significantly worse. It may be caused by the small amount of data I use for testing, so I want to ask in a normal amount ...
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Instance Segmentation using the predefined bounding boxes

I want to do Instance Segmentation using the images in my dataset which are already annotated and I don't want to train the model but use the pre-trained model. I was following this colab notebook. ...
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Understanding Object Detection Chart Showing Category Percentages "As Total Detections Increase"

I'm trying to understand the following picture, which comes from the "description of updates" pdf on this site for "Diagnosing Error in Object Detectors" by Derek Hoiem, Yodsawalai ...
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Why YOLO algorithm predicts B boxes for each grid cell S?

In yolo each grid cell predicts multiple bounding boxes lets say in YOLOv1 it predicts B=2, what is the advantage as it only predicts class probabilities only once for each grid cell. If that so why ...
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Uniform detection: a starting point?

Given an image of a worker, I need to verify if he/she is wearing the company's uniform. I tried to Google, but either the search results are about uniform sampling or some object detection tutorials. ...
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Object Detection - How to evaluate saved model weights?

I've recently completed training an object detection model but only printed out the losses for each epoch. Since I have the saved model weights, how would I go about evaluating the accuracy/precision? ...
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How to resize image along with their mask?

I have original images of the size 1935x1481. I am using labelme to annotate the images. I am creating polygons on the original image. Is there a way to resize the image along with their mask? I am ...
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Count repeating "objects" in a picture

This is my first data-science project and I would love to get some guidance to know how to get started. My problem is the following: I want to count objects that are in a picture. This picture has a ...
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40 views

Small object detection preprocessing

I am currently working on an object detection project in which I amtrying to detect very small objects 50x50 object in a 2k image. EfficientDet produced a very low result if I just put the raw ...
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Automated tools to generate synthetic training images out of synthetic 3D models and 2D backgrounds

I have 3D meshes and textures for a dozen of objects, which have to be detected in synthetic images. I have 2D textures of backgrounds these objects will be visible in front of. Object detection will ...
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How to annotate the object more efficiently

I want to perform object detection and object counting on the given below image using neural networks. My first step will be to annotate and label each object present in the training set of images. In ...
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Value of AP and AR are -1.000 in evaluation

As I understand, the AP amd AR calculation are as of follow: ...
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Train object detection to detect floor type

What is the best approach to train object detection to efficiently detect floor type in an image (e.g., hardwood floor, tile floor, etc.)? I don't need a full mask or bounding box, I just need to ...
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What is the difference between Salient and Generic Object Detection?

There are two types of Detection methods in general. Generic and Salient. Question: What is the exact difference in between the two? Broad Difference:
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How can I use COCOAPI/PyCOCOTools to evaluate the performance of Tensorflow Lite models

I have used the Tensorflow Object Detection API to train models on a custom dataset. The tensorflow object detection API also allows evaluating the trained models on a test set and gives results in ...
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How to convert classification maps to bounding box

I have a fully convolutional network that has been trained to classify cats and non-cats in small images (48x48). Because it is fully convolutional, I would expect that if I run it in bigger images, ...
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Scalable Infrence Server for Object Detection

I have created a Django service (nginx + Gunicorn) for object detection models. For my case i have 50+ models with resnet 50 based back bone. Server Machine Specification: 16 CPU 64 GB Ram I have ...
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Can't get a regression problem to converge

I am working on implementing a really simple version of YOLO to learn about pytorch and building deep learning models. My dataset consists of images which have two MNIST digits placed somewhere on the ...
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What is the difference between a bounding box and ROI (Region of Interest)

I was reading about the Fast RCNN for object detection. From what I understand, it uses pre-computed ROI's (using selective search) and uses these to predict the bounding box offsets and uses smooth ...

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