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.

Filter by
Sorted by
Tagged with
22
votes
2answers
13k views

What is the difference between semantic segmentation, object detection and instance segmentation?

I'm fairly new at computer vision and I've read an explanation at a medium post, however it still isn't clear for me how they truly differ.
12
votes
5answers
6k views

Unsupervised image segmentation

I am trying to implement an algorithm where given an image with several objects on a plane table, desired is the output of segmentation masks for each object. Unlike in CNN's, the objective here is to ...
8
votes
3answers
12k views

what is darknet and why is it needed for YOLO object detection?

what is darknet and why is it needed for YOLO object detection ? I read that its a neural network written in C , but why is it needed for YOLO object detection when we have lot of machine learning ...
8
votes
5answers
3k views

How can we extract fields from images?

I am making an document parser which extracts data fields from the documents and store them in a structured way. Each field in my dataset is horizontal which is easy to extract. But the model fails ...
8
votes
4answers
4k views

Faster-RCNN how anchor work with slider in RPN layer?

I am trying to understand the whole Faster-RCNN, From https://www.quora.com/How-does-the-region-proposal-network-RPN-in-Faster-R-CNN-work Then a sliding window is run spatially on these feature ...
5
votes
1answer
1k views

Does image's background matter for detector training (CNN)?

Does an image's background matter for detector/localisation in the training part (using CNN)? For example, if I want to make a face detector, which one is better as training dataset? Faces cropped ...
5
votes
1answer
5k views

What is the difference between tensorflow saved_model.pb and frozen_inference_graph.pb?

I've re-trained a model (following this tutorial) from the google's object detection zoo (ssd_inception_v2_coco) on a WIDER Faces Dataset and it seems to work if I use ...
5
votes
2answers
81 views

Keyword localization in audio file

I want to build a model that can localize occurrences of a particular word in an audio file. For example, I want to find the word "pizza" in a ~5min recording. The program should return an array with <...
5
votes
2answers
591 views

What is difference between intersection over union (IoU) and intersection over bounding box (IoBB)?

Can someone give a detailed explanation IoU and IoBB along with that the differences between them.
5
votes
1answer
1k views

Smart data split (train/eval) for Object Detection

I am looking for a smart way of splitting object detection data (images with labelled objects inside them) while taking into account the distribution of the objects themselves and not just the images. ...
4
votes
1answer
12k views

mAP scores on tensorboard (Tensorflow Object Detection API) are all 0 even though the loss value is low

I trained a faster-rcnn model on the tensorflow object detection API on a custom dataset. I found that the loss is ~2 after 3.5k steps. However, when I ran eval.py, the mAP scores are all almost 0 as ...
4
votes
1answer
5k views

Creating a Object Detection model from scratch using Keras

I have a dataset containing 330 images which contain guns. Along with the images, I have a text file associated with each image file which contains, The number of objects ( guns ) in the image. ...
4
votes
2answers
3k views

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 ...
4
votes
1answer
3k views

Which is the "BEST" deep learning model for "Custom" object detection for images & real time. YOLO v3, v4, v5, EfficientDet?

Whenever I look for object detection model, I find YOLO v3 most of the times and that might be due to the fact that it is the last version created by original ...
4
votes
1answer
1k views

Preparing ground truth labels for YOLO3

I want to train YOLO3 for a custom dataset that has raw labels in JSON format. Each bounding box in JSON is specified as [x1, y1, x2, y2]. So far, I have ...
4
votes
0answers
363 views

Find missing object(s) in image with a priori knowledge about the missing object(s) (w.r.t base image)

Problem Statement: I am working on developing a method, or borrow/modify/combine existing ones, where given an golden image (reference or base with all expected objects to be present), it is able to ...
3
votes
2answers
348 views

Best neural network architecture for object detection without location

I want to build a model which is able to detect the presence of a specific object in the image without caring about the location (i.e. no bounding boxes, just 0/1 output). More specifically, the ...
3
votes
1answer
35 views

Faster RCNN-RPN NETWORK

I already asked this question in stack overflow, but got response from experts, to post this question here, please help me to understand this concept... I am trying to understand RPN network in Faster ...
3
votes
1answer
3k views

Sliding window Algorithm and its convolutional implementation

I want to know why the convolution implementation of the sliding windows is equivalent to the sequential step-by-step sliding window? Why are they the same thing? I'm following Andrew NG for this: ...
3
votes
1answer
232 views

How to label "other" while labeling image for object detection/classification?

I want to train a model to recognize the different categories of food e.g. rice, burger, apple, pizza, orange and other things. After the first training, I realized that the model is detecting other ...
3
votes
1answer
160 views

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 ...
3
votes
1answer
345 views

Implementation of the paper 'Perceptual Generative Adversarial Nets for small object detection'

I studied the research paper on Perceptual Generative Adversarial Nets for small object detection. There they have detailed the structure of Generator network as given in the picture below: I am new ...
3
votes
1answer
164 views

What is wrong with my Precision-Recall curve?

Hi, I found this: https://github.com/rafaelpadilla/Object-Detection-Metrics I prepared my data: ground-truth and prediction files with bounding boxes. but I got a very strange plot. What do you thing?
3
votes
1answer
221 views

Get bounding boxes for adjacent instances of a single class in image

I have a dataset with thousands of music score pages and manually annotated bounding boxes for the individual bars: My objective is now to train a DNN that should ultimately be able to get these ...
3
votes
2answers
4k views

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 ...
3
votes
0answers
148 views

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 ...
3
votes
1answer
55 views

How to train YOLOV4?

I am going to write yolov4 real-time object detection, and I have to do it for car then vehicle plate number, but it does not have to find plate number if there is no car, first car then number on car,...
3
votes
1answer
53 views

Can I train a CNN to detect the number of objects without localizing them first?

So I was trying to search but couldn't find any answers. I was wondering if it possible to train a model to detect the number of items of interest in a photo without having bounding boxes or dots to ...
3
votes
2answers
91 views

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 ...
3
votes
0answers
761 views

Bounding box regression in R-CNN

In R-CNN paper, they give the definition of the target values for bounding box regression Given that $(P, G)$ is a (prediction box, ground-truth box) pair of the form $(x, y, w, h)$ where $x, y$ is ...
2
votes
2answers
96 views

Creating a custom dataset for object detection

I'm currently trying to build a model to recognize approximately 10 labels (food items) in a fairly controlled environment (refrigerator). I was unable to find datasets that worked well enough for my ...
2
votes
1answer
36 views

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 ...
2
votes
1answer
45 views

Using the whole dataset for testing (not validation) in case of small datasets

for an object detection task I created a small dataset to train an object detector. The class frequency is more or less balanced, however I defined some additional attributes with environmental ...
2
votes
2answers
53 views

"Object" Detection in Textual Data

I have a task where the input is a parsed document (i.e., full text in 1 string or tokens) and I need to classify parts of the text into say 5 classes (i.e., 5 tokens from the entire text are labeled ...
2
votes
1answer
49 views

Playing cards object detection problem

I'm trying to train an object detection model to detect some of playing cards for example it will detect 1,2,3, king, queen and jack. And I'm making a class of not and I have put examples of other ...
2
votes
1answer
254 views

How YOLO training and prediction works for an object fall in multiple grid?

So far what I understood about YOLO, it expects training image should be divided in to fixed grid, where each grid has Label like P(object present or not), object bounding box, object classes. ...
2
votes
1answer
320 views

What's the difference between Haar-like Features and Haar Cascades?

Are they the same in terms of their algorithm? Or do they differ in their respective detection methods?
2
votes
1answer
1k views

Very slow convergence with CNN [closed]

I am new to deep learning. I am working on training an SSD model on a set of small objects. I am using Adam gradient descent for optimization and a large input (800x800), but I seem to only get an ...
2
votes
1answer
3k views

Preparing custom dataset for object detection using ML

Seeking clarity on single class object detection model using ML. I have prepared a custom database for this purpose up to 400 images which is split in 80%-20% as training and testing data-set. These ...
2
votes
1answer
57 views

Classifying objects in video without machine learning

Recently, Nick Bourdakos posted a series of videos demonstrating bottle detection in a video stream using Tensorflow.js. Specifically, he is using SSD-mobilenet. The problem could be summarised as ...
2
votes
1answer
563 views

How to use Tensorflow Model Zoo frozen graphs in an Estimator pipeline?

As Tensorflow* says on their website, the Estimators API should genereally make most ML tasks more friendly. In the past I've been using Tensorflow's Model Zoo for object detection as I didn't (and ...
2
votes
1answer
133 views

How to detect different brands of milk

I'm trying to create a object detection model to detect different type of milk. What is the best approach to achieve the result in the picture below? As you can see in the picture, this model did ...
2
votes
1answer
164 views

what is the best approach to detect small objects with similar shape?

I'm working a model which detect different products in supermarket shelf. In the training data, there are a lot of objects with similar shape placed very close to or stacked to each others.(eg: milks ...
2
votes
2answers
908 views

Do you apply confidence threshold before calculating mAP for YOLOv2?

I've been using YOLO v2 for object detection and have been trying to use mAP for validating the model. For training I use a confidence threshold of 0.25, however I am unsure as to whether to apply ...
2
votes
2answers
2k views

How to download images and bounding boxes from imageNet?

I am doing object detection for a specific class, say, chairs . I want to download images of chairs from imageNet. I also want to download the annotation xml files ...
2
votes
0answers
24 views

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. ...
2
votes
1answer
57 views

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 ...
2
votes
0answers
24 views

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. ...
2
votes
1answer
191 views

YOLOv3 Predicting bounding boxes for grid containing multiple centers

I recently started learning about YOLO and object detection, and I am kind of stuck on something. I was wondering if someone could explain to me what happens when a grid cell contains the centers of ...
2
votes
0answers
52 views

What is the difference in computational cost at inference time between object detection and semantic segmentation?

I am aware that YOLO (v1-5) is a real-time object detection model with moderately good overall prediction performance. I know that UNet and variants are efficient semantic segmentation models that are ...

1
2 3 4 5 6