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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Video / image recognition: Featurize movement
How would it be best to featurize movement of objects between video frames?
Let's say I have a footage of a wolf pack and I am trying to understand where the Alpha is there. The best is actually not ...
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How to choose our data set wisely?
I have a couple of questions and I was wondering if you could answer them.
I have a bunch of images of the cars (side view only). I would like to train a model with those images. My objects of ...
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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?
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YOLO v3 complete architecture
I am attempting to implement YOLO v3 in Tensorflow-Keras from scratch, with the aim of training my own model on a custom dataset. By that, I mean without using pretrained weights. I have gone through ...
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Issues related to the code for ROI pooling from the feature map
I am trying to do ROI pooling on the feature map obtained from the VGG layers but I don't know how to code this layers. Can anybody help me out?
Here is my VGG layers:
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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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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 ...
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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 ...
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Is it ok to use photo collages as dataset instead of single images for training the object detection ssd model?
Is it normal/better to use photo collages (multiple photos in one image) as a dataset instead of single images for training the object detection SSD model?
I am using Tensorflow Object Detection API ...
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On which data evaluate an object detection model ? (similar or real life data ?)
I'm training an object detection model (SSD300) to detect and classify body poses in thermal images.
Even I have more than 2k different poses, the background does not change much (I have only 5 ...
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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 ...
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YOLO Dense Prediction
I have two questions about dense prediction in YOLOv4 paper
What does it mean by the (hard negative, online hard) example mining method is not applicable to one-stage object detector, because this ...
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Training object detection models from the scratch without using pre-trained models and weights
I have a data set of 25 images. I wish to run Faster RCNN or yolov3 object detection models on this images.I want to create my custom trained model and get weights after running say 10 epochs. Later I ...
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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 ...
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Curve of MAPs to evaluate training progress of Mask RCNN on synthetic data
Is MAP (Mean Average Precision) a good substitute for measuring training and validation accuracy at different stages of training a machine learning model for object detection?
I am retraining a Mask ...
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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 ...
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Train a point rather than a bounding box for object detection
In the graph below, object detection is done through a point that points to the right place rather than a bounding box (e.g., using faster RCNN). What method enables to train such a point?
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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 ...
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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 ...
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How can we create an label, value detector?
I am trying to implement an text detector using MaskRCNN such that the model detects the label and value as shown in the image below.
Detecting the same is easier for fields like page date and order ...
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Detect Objects on a table
is it possible to train a model which detects and draws bounding boxes for objects on a table, when I use a dataset where objects on a table are labeled with boundingboxes?
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Average Precision if Target Class is Not in Evaluation
Suppose I have 5 classes, denoted by 1, 2, 3, 4, and 5, and this is used in object detection.
When evaluating an object detection performance, suppose I have classes 1, 2, and 3 present, but classes 4 ...
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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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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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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 ...
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Is there any paper of object detection that detect not trained class or object?
After reading some object detection papers (kinds of R-CNN, YOLO,...) I'm wondering if there is a detector that detects objects ...
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How to obtain and load a good initial data set for object localization?
I'm looking for a good data set for training a CNN based network to do object localization (i.e. a data set with class labels and bounding box data).
What is a good initial data set to use?
How can ...
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Why yolo4 pytorch re-training loss seems high as like first time training?
I had a setup a yolo4 pytorch framework in google colab by cloning git clone https://github.com/roboflow-ai/pytorch-YOLOv4.git.
I generated checkpoints by giving ...
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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 ...
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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 ...
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How to collect a computer vision dataset?
Context: my team is researching some plant-growth patterns using object detection models. We have collected a small set of images (a few thousand) and ran some simple experiments. The results were ...
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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 ...
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Extracting structure and content from invoices
Lately, I have been largely inspired by this https://rossum.ai/, which is able to extract text from invoice documents.
Do you have any ideas on how this could be implemented? It's clear that they ...
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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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Feature extraction in machine learning
I am a bit confused by reading A survey on object detection in remote sensing. They state that machine learning-based object detection consists of three essential parts - feature extraction, feature ...
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Understanding 'scale_boxes' in YOLO Algorithm of CNN
I'm studying Andrew NG's Convolutional Neural Networks and am in Week 3 of the course which deals with object detection using YOLO algorithm . I don't understand one section in the programming ...
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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 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. ...
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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 ...
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Detecting address labels using Tensorflow Object Detection API
I am experimenting with the Tensorflow Object Detection API on a Windows 7 machine. I am trying to detect US address labels (and similar blocks of text) as they appear on a piece of mail or an ...
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Better to crop or compress training data?
I've been trying to make an object recogniser in Tensorflow and have used labelImg to classify large electrical transmission towers at varying distances. In order to make 10-16MP (~2-7MB) images train ...
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Training Object Detection model on just 10 images
I am trying to train an object detection model using Mask-RCNN with Resnet50 as backbone. I am using the pre-trained models from PyTorch's Torchvision library. I have only 10 images that I can use to ...
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SSD based on ResNet-101 doesn't improve over SSD-VGGNet
I am training a SSD model for detecting mobile cranes.
The training dataset contains 1,000 images and test set over 400 images.
About 200 epochs gave mAP 83%, but my target is 90%.
So I trained SSD-...
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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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Why are axes-aligned bounding boxes used in object detection
I understand (I think) why in object detection, the result is a rectangle:
it is a simple shape that can be defined by 4 variables (2 pairs coords of opposite corners or 1 pair of coords + width and ...
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What are the 'protos' in TF Object Detection?
I am struggling to understand what are the 'protos' in TF Object Detection?
Why do we need them here?
Also, while setting up the TF API we need to download and compile protocol buffers.
There is also ...
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Why does my mAP metric value start so high in the first epoch?
I am doing an object detecton task and I have an issue with my mean average precision metric (mAP). The problem is that the value is a perfect 1.0000 from the first epoch. My guess is that it has ...
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Difference between text-based image retrieval and natural language object retrieval
I am working on creating a model that locates an object in the scene (2D image or 3D scene) using a natural language query. I came across this paper on natural language object retrieval that mentions ...
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What am I supposed to see on tensorboard images tab?
I'm training an object detection model with Tensorflow and monitor the training task with tensorboard. I was expecting in the Images tab of tensorboard that displayed images would show a bounding box (...
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