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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How to use computer vision datasets like MSCOCO for object detection?

Im currently trying to understand tensorflow and specific the Tensorflow Object Detection API. I understood that I need annoted images which define regions of interest. Now I'm thinking about trying ...
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Object Detection: Unusual warning while training Detectron2 Faster R-CNN

I am trying to train a Detectron2 faster_rcnn_R_50_FPN_3x model on a custom dataset, pretrained on PublayNet Dataset. While training, I am getting the following warning: ...
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Cannot test custom object detection model

I am using this tutorial: https://gilberttanner.com/blog/tensorflow-object-detection-with-tensorflow-2-creating-a-custom-model . I have trained the model but when I try to test it with this command: <...
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Any way to make NER tagging with float(2.0) and inferencing with str(2)

One of the NER attribute is tagged with float (3.0, 2.0, ...) while the text file I am trying to inference from are in string format of (3, 2, ...). The Spacy model I used can't pick up the numbers ...
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Can you use a Confusion Matrix for a image detection problem?

I have read the classic examples of using a Confusion Matrix for a classification problem. ("Does a patient have cancer, or not?) The ML system I am working with is for detecting objects in an ...
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Find the Outlier

I have data that contains points (geo coordinates of a random planet, integer pairs) that represent places where land is definitely there. Here is an example with ...
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3D object detection for 2D images (logistics use case)

I am working on 3D object detection for parcel boxes same like amazon parcel,thinking to label with 3D cuboids but finding difficult to find a existing 3D object detection for 2D images. As far what i ...
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How can seemingly arbitrary anchor box sizes be created out of a few scales and ratios?

I am struggling with understanding a certain aspect of anchor boxes. Anchor boxes are generated from a list of predefined ratios and scales. For example: ...
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How to arrange ground-truth for anchor box representation in object detection

I am working on CharGrid and BERTGrid papers and have questions about bounding box regression decoder part. In the CharGrid paper, it states that there are two outputs from this branch: one with ...
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Is it possible to strip/supress embedded bounding boxes from images?

I'm doing a project that needs to use this company's CCTV image samples to build my own object detection model, although the provided images all have red/green bounding boxes baked into the jpg's with ...
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Should Non-Max Suppression (NMS) be tuned as a hyperparameter?

This may be a silly question, but when tuning hyperparameters for an object detection model, should we tune the NMS threshold, or is this better left to tune by hand afterwards? For region-proposal ...
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Object detection or image classification? Each image has 3 shapes. I want to return 1 if they are all triangles, 0 otherwise

Question is in the title. Every image has three shapes, which can be either triangles or squares. I want to return 1 if all shapes are triangles, 0 otherwise. Which do you think would work better for ...
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Yolov5 image detection without segmentation?

I have read a number of papers on Yolov5 images detection techniques. But the papers don't refers to any segmentation step done by Yolov5. While I know that it is not possible to do image ...
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Can I send images + boundingboxes(as features) to an LSTM? How?

I have previously trained a YOLO v4 object detection model and I am looking to leverage the results(Bboxes) of this model and create another model to recognize/classify accidents in CCTV footage/video(...
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How to annotate complete images?

I am currently playing around with tensorflows object detection to learn the basics. Now I've set myself the goal to detect letters in computer written text. For example the header of a newspaper ...
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Increase accuracy through "overfitting" multiple models?

I am currently trying to create a model to classify 5 specific classes from the coco dataset. I am using the object detection app from tensorflow. My question is: Will it be better if i: -Train one ...
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Is it possible to perform additional learning on a pre-trained model with YOLO based on Darknet

I would like to have a capability of my object detection model to improve over time as the available dataset grows over time, but avoid re-training a model from scratch every time I want to update the ...
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How to extract specific region from black and white image using openCV

I have been trying to learn OpenCV as I have a deep interest in Computer Vision and one of the problems I have been trying to figure out is how to extract a particular region of an image with OpenCV. ...
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Object Detection, custom dataset, algorithm [closed]

I'm looking for a solution to detect objects and classify them, using a custom dataset.The overall goal is to detcet objects using my webcam. So far I've wanted to use YOLO in combination with OpenCV, ...
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How to convert horizontal bounding box coordinates to oriented bounding box coordinates

I am trying to detect oriented bounding boxes with faster rcnn for a long time, but I could not make it to do so. I aim to detect objects in the DOTA dataset. I was using built-in faster rcnn model in ...
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How can I correctly identify an item within a larger image, but also detect if the item is the correct orientation?

I have some machinery at work with a small sticker I am trying to detect within a larger image. I am familiar with object detection techniques based on a trained classification model, but to further ...
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Average Precision i -1

I am new to this. I tried to train an SSD mobilenetv2 model using tensorflow object detection API. I followed this colab notebook https://colab.research.google.com/drive/...
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When using Jupyter (R kernel) and the keras library. When a cell is run there is no output. W/no output, there's no way knowing code functions.?

The keras digit object detection code does actually run in Jupyter using the R kernel. But it took three attempts to recognize that there wasn't an issue with Jupyter, or the R kernel, or the code. ...
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Speech/Voice Detection in Audio Files

I have several hundred 30 second long WAVE Files. I need a way to find out, if there are spoken words / voices / speech in them or not. E.g.: 1.wav no; 2.wav yes; 3.wav no (boolean) or 1.wav 0.21; 2....
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U-net cannot detect midline of large object

I am training a three-dimensional U-net to detect tube-shaped objects, such as blood vessels, in medical image data. I am using simulated images during training, which contain tubes of varying size, ...
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How to identify precision, recall, IoU, and mAP in these results for my trained Tensorflow model?

I have trained a Single Shot Detector model (using Tensorflow), and have run the evaluation metrics. However, I am not entirely sure what to make of them. Doing a computer vision literature search, ...
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SSD-300 tensorflow mAP is very low due to unstable loss

I am training my SSD-300 model for which I have resized images to 300x300. I am using the default settings as mentioned in github repo: https://github.com/balancap/SSD-Tensorflow The loss is unstable ...
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Using Object Detection or Image Segmentation without labelled input data to build a dataset to then be manually labelled?

I'm looking to build an object detection model or image segmentation model, ideally the latter, which will identify and label objects from satellite imagery but I don't currently have any labelled ...
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Reduce Training steps for SSD-300

I am new to deep learning and I am trying to train my SSD-300 (single shot detector) model which is taking too long. For example even though I ran 50 epochs, it is training for 108370+ global steps. I ...
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Soft-NMS during Inference

I have read the paper about the soft-NMS and the problem that tries to solve. Does it make sense to use this algorithm during inference apart from training? It smooths the predictions on the bounding ...
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Heterogenous data between classes in object detector

I have created a synthetic dataset for object detection with about a dozen classes by placing models of the classes in front of random images (from the MIT Place2 dataset) in Blender. This is working ...
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Does having two different models improve performance for underrepresented classes?

I am currently working on a dataset that has approximately 7000 annotations, but suffers from severe class imbalance (there are 1331 annotations for the most represented class, and 77 for the least ...
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How can I detect symbols/icons on a label?

Given this label: How can I identify that the CE mark is there? I've tried template matching with OpenCV but results are quite inconsistent because of symbol-template size differences (scaling & ...
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Activation Maps using Tensorflow Object Detection API

I am trying to create visual explanations such as GradCAM from a trained object detection model. In order to implement the algorithm I need to access intermediate tensors and calculate gradients to ...
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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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