Questions tagged [object-recognition]
The object-recognition tag has no usage guidance.
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Which approach to determine the size of an object to be placed given the sizes of the existing objects in a scene?
I am working on an automated approach to object-based data augmentation. The goal of the approach would be to add a selected object to an existing image. To automate this task, information is needed ...
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How can I separate and follow the plants that are very similar to each other with the YOLOv5 algorithm?
I want to differentiate between fern and mint using the YOLOv5 algorithm. Now I can take pictures of fern and mint, mark them on LabelImg, and train them in collaboration with Google. However, since ...
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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 ...
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Should training images contains single or multiple object instances?
I'm pretty new to ML so I apologize for the potentially trivial question; I've been unable to find a clear answer to my question.
Let's imagine that I want to build a model that is able to detect ...
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Classification: ClassA vs. "everything else"
I am trying to create a neural network for recognizing a particular object. Maybe I am approaching this task from the wrong side, but, in my mind, this task boils down to teaching the network to do a ...
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DeepSORT features
I'm reading about Detection and Tracking algorithms and I'm unclear about the DeepSORT algorithm:
How does the DeepSORT algorithm gets the features? Does it "hijack" the feature vector from ...
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Object Detection without annotations and labels
Problem Statement:
I am given 2 sets of images. All the images in both sets are without annotations and labels.
First set : a set of images of the grocery store shelves (captured in the grocery stores)...
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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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Pre trained vehicle detection from low altitude view
I have a very noob question. I need some solution to detect all vehicles in the video (or at least in the image).
I have tried YOLOv3, however, it cannot recognize cars from the top (like that in the ...
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Estimate the location of an object in a field using computer vision and math
I'm trying to see how to detect the location of a soccer ball in the field using the live camera. What are some ways to achieve this? At this point I'm more interested in ideas and thoughts and not ...
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TF object detection - The total number of detected objects is not increasing
I'm building a model to recognize fishes in the aquarium (150 different fishes).
I'm using a faster_rcnn_inception_v2_coco_2018_01_28 model for transfer learning from TF object detection API. I have ...
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How can you include information not present in an image for neural networks?
I am training a CNN to identify objects in images (one label per image). However, I have additional information about these images that cannot be retrieved by looking at the image itself. In more ...
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why we have run make.sh file initially in darknet and YOLO object detection?
In have seen a couple of text and objection detection algorithm wher the first step everyone dose is to install cython and run a make.sh file . why we have run make.sh file initially in darknet/YOLO ...
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optical chemical structure recognition from images
I want to recognize name of the chemical structure from the image of chemical structure, like in the given image it is benzene structure I want to recognize that it is benzene from the image(I should ...
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Using context to improve object detection and image classification
we are building an image classifier using the Tensorflow Object Detection API.
Our images often appear in groups, e.g. a cluster of dogs playing in the grass. Ofter our model will recognize some of ...
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Recommendations to generate a training set of images
We are about to start a series of experiments in physics which will generate 8.5 thousands of images per month. This is a study on microscopic material reactions so the images are not 'normal' objects ...
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Does resizing images during training affect the bounding box annotations?
I am using the TensorFlow object detection API to train my own custom dataset and am preparing annotations for the same. I see from the config file of my pre-trained SSD inception net, the size of the ...
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Similar objects same labels
Example: red paprica and green paprica. The output I need is just paprica, should i label them the same or give them two labels "green paprica" and "red paprica" and leater on just treat them as one? ...
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Face detection for different poses more robust than MTCNN?
I am using the MTCNN model described on machinelearningmastery here: MTCNN ipazc
But it won't detect certain orientations, ie. somebody lying on the ground so the top of the head points to the right ...
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Why is a general/original softmax loss not preferred in FR (face recognition)?
In some papers I've read that softmax loss is not preferred in FR since it does not give a good inter-class and intra-class margins, but could not understand 'why?'. So can someone explain, why ...
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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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How to generate Anchor boxes for SSD?
I am currently trying to understand the method of generating anchor boxes for object detection. I am looking at a code where the author has done this task in a very flexible way. But I am having ...
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mean average precision - pseudo code
There are many blog posts and threads concerning the computation of mAP, both for PASCAL and for COCO. Still, they do not answer some fundamental questions.
I am listing here the flow as I understand ...
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Mask RCNN: Random predictions during inference for the same image
I recently trained the Mask RCNN (matterport's implementation) on some satellite images, but during inference mode, I'm getting random predictions for the same set of weights for the same image.
That ...
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Bounding Boxes in YOLO Model
The YOLO model splits the image into smaller boxes and each box is responsible for predicting 5 bounding boxes.
My question is how does the model make these bounding boxes for every grid cell ? Does ...
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How to prepare photo data for training model to recognize bowling ball name, brand and manufacturer from photo of bowling ball?
I am asked to do this. The client can only prepare a only one photo for each ball from the product page of bowling manufacturer.
However, I need huge amount of image data for each ball.
Here is ...
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Add training data to YOLO post-training
I've been playing around with YOLOv3 and obtaining some good results on the ~20 custom classes I trained. However, one or two classes look like they can use some additional training data (not a lot, ...
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What does the co-ordinate output in the yolo algorithm represent?
My question is similar to this topic.
I was watching this lecture on bounding box prediction by Andrew Ng when I started thinking about output of yolo algorithm.
Let's consider this example, We use ...
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Detecting directions using Convolutional neural networks [closed]
I am working on a task where I have to detect damages on the vehicles and exactly where the damage has occurred. So I have to not only detect the damage on the door but also mentioned which door(front ...
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In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?
I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of ...
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Object Detection classification
I am currently training a classifier for detecting resistors using TensorFlow Object Detection API. For that, I downloaded resistor images from ImageNet and I am currently labeling those who will be ...
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How does the bounding box regressor work in Fast R-CNN?
In the fast R-CNN paper (https://arxiv.org/abs/1504.08083) by Ross Girshick, the bounding box parameters are continuous variables. These values are predicted using regression method. Unlike other ...
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Python : Feature Matching + Homography to find Multiple Objects
I'm trying to use OpenCV via Python to find multiple objects in a train image and match it with the key points detected from a query image. For my case, I'm trying to detect the tennis courts in the ...
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How does YOLO algorithm detect objects if the grid size is way smaller than the object in the test image?
In YOLO algorithm how do these grids output a prediction if some grids only see a small black portion of the car if the model was trained on datasets with full images?
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Tensorflow Object Detection API
Looking at the Tensor-flow object detection API, and walking through the "How to train your own Object Detector" for raccoons, which is a handy guide to get you up and running.
What I would like to ...
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How does region proposal network (RPN) and R-CNN works?
I would like to know where I could find useful articles/papers about the basic concepts of RPN and R-CNN.
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How to calculate mAP for detection task for the PASCAL VOC Challenge?
How to calculate the mAP (mean Average Precision) for the detection task for the Pascal VOC leaderboards?
There said - at page 11:
Average Precision (AP). For the VOC2007 challenge, the interpolated
...
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Pre trained vehicle detection network
I'm looking for a pre-trained net recognizing vehicles, something like the Inception network for images.
If that is impossible to find which vehicle detection algorithm would you suggest, possibly ...
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Is there something like class-based object detection? Or class-based selective search?
I've been reading a lot about computer vision lately, and while there is a huge amount of info about object classification, and a lot less on object detection, I have not found anything on class-based ...
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Faster R-CNN: Labels regarding the positive anchors when there are many classes
The authors of the original paper of Faster R-CNN when they refer to the positive anchors, they are labeled as 1. I guess they refer in binary classification. What happens in the case in a task we ...
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What are the model configuration parameters in tensorflow object detection API?
In the Config file there are some parameters which I don't understand properly . I will mention them here.
first_stage_features_stride - Is this the ration of input/output ?
height_stride (In the ...
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Human face attractiveness estimation
Needed for dating portal. I currently use OpenFace to extract features with DNN. (I don't know whether they have a usable meaning) Then compare them to some model faces' features using euclidian ...
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Train object detection without annotated data/bounding boxes
From what I can see most object detection NNs (Fast(er) R-CNN, YOLO etc) are trained on data including ...
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What does it mean if performance of two different iterations of the same network (CNN model) varies a lot?
So I trained CNN model for people detection on caltech-pedestrian dataset:
Then I was curious and evaluated the model in every 1000th iteration on Evaluation toolbox(I guarantee, there is no bug in ...
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what could it be a good descriptor for simple greyscale symbols?
I need to find a good method to extract key points from drawing symbols like elements in CAD drawings (eg in 2D objects for the bathroom that can be placed on a floor plan).
I've already tried all ...
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Why is video classification still not that accurate?
I was wondering, with the advent of deep learning, many tasks related to images have been solved to near human accuracy such as classification, object detection etc., however in videos, traditional ...
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Algorithm to create graphics from scribble
I want to implement a system that takes as input scribbles (i.e. drawings with writings on paper, input to the algorithm is a photo of this) and outputs the forms / writings e.g. in Powerpoint.
What ...
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Objects Localization Through CNN
I am new to deep learning and tensor flow and I am trying to train a CNN at localizing digits in the Street View House Numbers data set. To this end I have an input set of 32x32 images and, since I ...
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What techniques to use for image matching
I have a database with around 30,000 pictures. All of them are a different object. They are all from a certain perspective, the pictures itself are the same size but the objects vary in size. I want ...
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