Answers.Body: <p>The computer vision problem that you are describing is <strong>object detection</strong>, i.e. the problem of finding the location of specific objects in an image and label them correctly with their names.</p>
  <p>There are many resources on the web (or in books) that describe this problem more in detail and examples (which also include code) to get you started with it (e.g. <a href="https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html" rel="nofollow noreferrer">this one</a>).</p>
  <p>In any case, to solve this problem, you will (probably) need a <strong>labelled dataset</strong> <span class="math-container">$D$</span>. So, if you don't have it, you will need to (manually) collect many images, similar to the ones you describe, and find the objects of interest in them (i.e. their locations, which may be specified as a <em>bounding box</em>), and assign the corresponding name to each of them. At the end of this process, you should have a dataset of the form <span class="math-container">$D = \{(x_1, y_1), \dots, (x_1, y_1) \}$</span>, where <span class="math-container">$N$</span> should be as big as possible, <span class="math-container">$x_i$</span> is an image, and <span class="math-container">$y_i$</span> are the labels (also known as <em>targets</em>), which, in this case, should be both the location and name of all objects of interest in <span class="math-container">$x_i$</span>. The specific format of the labels depends also on the specific model that you will train to solve this problem. You can find different models online for this task, such as <a href="https://arxiv.org/pdf/1506.02640.pdf" rel="nofollow noreferrer"><strong>YOLO</strong></a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-10-13T16:05:04.583Z
Answers.LastActivityDate: 2021-10-13T16:05:04.583Z
Answers.UserDisplayName: nbro
Answers.Body: <p>If your object is relatively small in the entire image, Yolo version 2 could be one of choices. Here is <a href="https://www.reddit.com/r/computervision/comments/dhh1qp/detecting_very_small_objects_using_yolo_v2_in/" rel="nofollow noreferrer">one discussion</a> in Reddit.</p>
  <p>If you want to see other methods, please check out <a href="https://www.kaggle.com/competitions/airbus-ship-detection/code" rel="nofollow noreferrer">list of codes from the Airbus Ship Detection Challenge</a>.</p>
  <p>This list is from <a href="https://www.linkedin.com/in/nikolay-sergievskiy-32542159" rel="nofollow noreferrer">Nikolay Sergievskiy LinkedIn profile</a>. It looks like he was one of winners of <a href="http://xviewdataset.org/" rel="nofollow noreferrer">the DIU xView Detection Challenge</a> in 2018.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2023-11-03T00:05:09.423Z
Answers.LastActivityDate: 2023-11-03T00:05:09.423Z
Answers.UserDisplayName: Cloud Cho
Body: <p>What kind of algorithm or approach can I use to find a specific type of object in an image?</p>
  <p>In particular, I am interested in finding an object like a windmill in an image taken, for example, from Google Maps. The image could be something like this</p>
  <p><a href="https://i.sstatic.net/OCJ2P.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/OCJ2P.png" alt="Wind Turbine " /></a></p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2023-11-02T23:40:29.453Z
Comments.Text: If you already have images, what is the average object dimension in pixel?
Comments.UserDisplayName: Cloud Cho
Tags: <machine-learning><computer-vision><object-detection><algorithm-request>
Title: What kind of algorithm or approach can I use to find a specific type of object in an image?
UserDisplayName: S E
ThreadText: # What kind of algorithm or approach can I use to find a specific type of object in an image?
  
  (Asked by: username_0 on 2021-10-12)
  
  What kind of algorithm or approach can I use to find a specific type of object in an image?
  
  In particular, I am interested in finding an object like a windmill in an image taken, for example, from Google Maps. The image could be something like this
  
  [![Wind Turbine ](https://i.sstatic.net/OCJ2P.png)](https://i.sstatic.net/OCJ2P.png)
  
  **Tags:** machine-learning, computer-vision, object-detection, algorithm-request
  
  > **Comments:**
  > **username_1**: If you already have images, what is the average object dimension in pixel?  
  
  ---
  
  ## 2 answers
  
  ### Answer by username_2 on 2021-10-13. Score: 0
  
  The computer vision problem that you are describing is **object detection**, i.e. the problem of finding the location of specific objects in an image and label them correctly with their names.
  
  There are many resources on the web (or in books) that describe this problem more in detail and examples (which also include code) to get you started with it (e.g. [this one](https://pytorch.org/tutorials/intermediate/torchvision_tutorial.html)).
  
  In any case, to solve this problem, you will (probably) need a **labelled dataset** $D$. So, if you don't have it, you will need to (manually) collect many images, similar to the ones you describe, and find the objects of interest in them (i.e. their locations, which may be specified as a *bounding box*), and assign the corresponding name to each of them. At the end of this process, you should have a dataset of the form $D = \{(x\_1, y\_1), \dots, (x\_1, y\_1) \}$, where $N$ should be as big as possible, $x\_i$ is an image, and $y\_i$ are the labels (also known as *targets*), which, in this case, should be both the location and name of all objects of interest in $x\_i$. The specific format of the labels depends also on the specific model that you will train to solve this problem. You can find different models online for this task, such as [**YOLO**](https://arxiv.org/pdf/1506.02640.pdf).
  
  
  ---
  
  ### Answer by username_1 on 2023-11-03. Score: 0
  
  If your object is relatively small in the entire image, Yolo version 2 could be one of choices. Here is [one discussion](https://www.reddit.com/r/computervision/comments/dhh1qp/detecting_very_small_objects_using_yolo_v2_in/) in Reddit.
  
  If you want to see other methods, please check out [list of codes from the Airbus Ship Detection Challenge](https://www.kaggle.com/competitions/airbus-ship-detection/code).
  
  This list is from [Nikolay Sergievskiy LinkedIn profile](https://www.linkedin.com/in/nikolay-sergievskiy-32542159). It looks like he was one of winners of [the DIU xView Detection Challenge](http://xviewdataset.org/) in 2018.
  
  
  ---
  
  