Answers.Body: <p>Maybe try the COCO (common objects in context) dataset. 
  It's often used for object detection, segmentation and localisation. 
  They provide labels, and you can limit the size by downloading only a specific number of classes.
  <a href="http://cocodataset.org/#explore" rel="nofollow noreferrer">http://cocodataset.org/#explore</a></p>
  
  <p>It's also quite a common one, so you can expect good documentation, and online answers to your questions.</p>
  
  <p>Hope that helps!</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-02-03T12:42:58.023Z
Answers.LastActivityDate: 2020-02-03T12:42:58.023Z
Answers.UserDisplayName: SumakuTension
Answers.Body: <p><em>NDDS is a UE4 plugin from NVIDIA to empower computer vision researchers to export high -quality synthetic images with metadata.
  NDDS supports images, segmentation, depth, object pose, bounding box, keypoints, and custom stencils. In addition to the expo rter,
  the plugin includes different components for generating highly randomized images. This randomization includes lighting, objec ts,
  camera position, poses, textures, and distractors, as well as camera path following, and so forth. Together, these components allow
  researchers to easily create randomized scenes for training deep neural networks</em></p>
  
  <p><a href="https://github.com/yehengchen/DOPE-ROS-D435/blob/master/Synthetic-Data-UE4-DOPE.md" rel="nofollow noreferrer">https://github.com/yehengchen/DOPE-ROS-D435/blob/master/Synthetic-Data-UE4-DOPE.md</a></p>
  
  <p>You can create 3D synthetic dataset here.</p>
  
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Answers.CreationDate: 2020-02-05T15:36:26.337Z
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Answers.UserDisplayName: avinashsen707
Answers.Body: <p>There are various dataset available such as </p>
  
  <ol>
  <li><p>Pascal VOC dataset: You can perform all your task with these. 
  <a href="https://i.sstatic.net/WZ1Ho.png" rel="noreferrer"><img src="https://i.sstatic.net/WZ1Ho.png" alt="enter image description here"></a>
  size of the dataset is as  follows
  <a href="https://i.sstatic.net/vl0JT.png" rel="noreferrer"><img src="https://i.sstatic.net/vl0JT.png" alt="enter image description here"></a></p></li>
  <li><p>ADE20K Semantic Segmentation Dataset: you can perform only segmentation here
  <a href="https://i.sstatic.net/mwoHl.png" rel="noreferrer"><img src="https://i.sstatic.net/mwoHl.png" alt="enter image description here"></a></p></li>
  <li><p>COCO dataset: This is rich dataset but a size larger then 5 GB so you can try downloading using google colab in your drive and then make a zip file of data as less than 5 GB
  <a href="https://i.sstatic.net/3DwkV.png" rel="noreferrer"><img src="https://i.sstatic.net/3DwkV.png" alt="enter image description here"></a></p></li>
  </ol>
  
  <p>You can download all these datasets using Gluoncv easily.here <a href="https://gluon-cv.mxnet.io/api/data.datasets.html" rel="noreferrer">link</a>.</p>
  
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Body: <p>I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization.</p>
  
  <p>Can anyone suggest me a dataset less than 5GB? Or do I need to know anything before implementing these algorithms?</p>
  
Tags: <datasets><object-recognition><object-detection><resource-request>
Title: Small size datasets for object detection, segmentation and localization
UserDisplayName: 0xPrateek
ThreadText: # Small size datasets for object detection, segmentation and localization
  
  (Asked by: username_0 on 2020-01-30)
  
  I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization.
  
  Can anyone suggest me a dataset less than 5GB? Or do I need to know anything before implementing these algorithms?
  
  **Tags:** datasets, object-recognition, object-detection, resource-request
  
  
  ---
  
  ## 3 answers
  
  ### Answer by username_3 on 2020-02-02. Score: 5 | Accepted answer
  
  There are various dataset available such as
  
  1. Pascal VOC dataset: You can perform all your task with these.
     [![enter image description here](https://i.sstatic.net/WZ1Ho.png)](https://i.sstatic.net/WZ1Ho.png)
     size of the dataset is as follows
     [![enter image description here](https://i.sstatic.net/vl0JT.png)](https://i.sstatic.net/vl0JT.png)
  2. ADE20K Semantic Segmentation Dataset: you can perform only segmentation here
     [![enter image description here](https://i.sstatic.net/mwoHl.png)](https://i.sstatic.net/mwoHl.png)
  3. COCO dataset: This is rich dataset but a size larger then 5 GB so you can try downloading using google colab in your drive and then make a zip file of data as less than 5 GB
     [![enter image description here](https://i.sstatic.net/3DwkV.png)](https://i.sstatic.net/3DwkV.png)
  
  You can download all these datasets using Gluoncv easily.here [link](https://gluon-cv.mxnet.io/api/data.datasets.html).
  
  
  ---
  
  ### Answer by username_1 on 2020-02-03. Score: 1
  
  Maybe try the COCO (common objects in context) dataset.
  It's often used for object detection, segmentation and localisation.
  They provide labels, and you can limit the size by downloading only a specific number of classes.
  <http://cocodataset.org/#explore>
  
  It's also quite a common one, so you can expect good documentation, and online answers to your questions.
  
  Hope that helps!
  
  
  ---
  
  ### Answer by username_2 on 2020-02-05. Score: 1
  
  *NDDS is a UE4 plugin from NVIDIA to empower computer vision researchers to export high -quality synthetic images with metadata.
  NDDS supports images, segmentation, depth, object pose, bounding box, keypoints, and custom stencils. In addition to the expo rter,
  the plugin includes different components for generating highly randomized images. This randomization includes lighting, objec ts,
  camera position, poses, textures, and distractors, as well as camera path following, and so forth. Together, these components allow
  researchers to easily create randomized scenes for training deep neural networks*
  
  <https://github.com/yehengchen/DOPE-ROS-D435/blob/master/Synthetic-Data-UE4-DOPE.md>
  
  You can create 3D synthetic dataset here.
  
  
  ---
  
  