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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Does it make sense to have object detection model followed by a classification model
So i was working with the SKU110k dataset and i was required to identify the different items in the shelf as well but the SKU110k dataset only annotated shelf items but did not identify them. So i ...
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What is the "fast version" of ZFNet referenced in SPPNet and Faster R-CNN papers?
I'm reading old papers:
SPPNet: Link
Faster R-CNN: Link
In both cases, the authors refer to a "fast version of Zeiler and Fergus (ZF) Net"; specifically:
In SPPNet:
ZF-5: this ...
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Tracking people problem
I am trying to implement a system for counting people in a building using Python and OpenCV, but I have one problem. The system for tracking people doesn't work very well; it can't track a person all ...
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How to implement hard negative mining for PyTorch RetinaNet_v2 object detection model?
I am currently using the PyTorch object detection model retinanet_resnet50_fpn_v2. I want to implement hard negative mining, such that I take the top X images with ...
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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.
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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 ...
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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 ...
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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 ...
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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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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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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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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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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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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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