Following on from the last two parts of the Machine Learning Video Datasets series, part three focuses on where to get the right picture dataset to train your Machine Learning models.

Following on from the last two parts of the Machine Learning dataset series, part three focuses on where to get the right Video Datasets to train your Machine Learning models.

On this page, you’ll find a number of datasets as well as links to portals where you may choose the best video datasets for your projects. Enjoy!

dataset card

Here is the list of free 10 Video Datasets For Machine Learning

 

  1. LSUN (http://lsun.cs.princeton.edu/2016/)

 

This dataset is useful for scene comprehension in conjunction with auxiliary task initiatives (room layout estimation, saliency prediction, etc.).

 

The massive Video Database, which includes photos from several rooms (as shown above), may be downloaded by going to the website and running the script supplied, which can be found here.

 

Scroll down below the scene classification’ heading and click ‘README’ to view the documentation

and demo code for additional information about the dataset.

 

Get Database:https://github.com/fyu/lsun/blob/master/download.py

 

  1. ImageNet (http://video-net.org/)

 

The picture collection for new algorithms is organized according to the WordNet hierarchy, with hundreds of thousands of photos depicting each node of the network.

 

To download Video Database, you must first register on the site, then mouse over the ‘download’ menu dropdown and choose ‘original pictures.’ You can request access to the original pictures if you’re utilizing the datasets for educational or personal purposes.

 

Image Net is also hosting a competition on Kaggle right now – check it out here.

 

Get Database:http://video-net.org/

 

  1. LabelMe (http://labelme.csail.mit.edu/Release3.0/browserTools/php/dataset.php)

 

A big annotated Video Datasets may be found on this website.

 

However, downloading them is not simple. The dataset may be downloaded in two ways:

 

  1. Using the LabelMe MATLAB toolbox to download all of the pictures. You can customize the section of the datasets you wish to download using the toolbox.

 

  1. Using the LabelMe MATLAB toolbox to use the pictures from the internet. This is a less favored method since it is slower, but it allows you to see the Video Datasets before downloading it. After you’ve installed the database, you may read the annotation files and query the pictures with the LabelMe MATLAB toolbox to extract specific items.

 

Get Database:http://labelme.csail.mit.edu/Release3.0/browserTools/php/dataset.php

 

  1. Indoor Scene Recognition (http://web.mit.edu/torralba/www/indoor.html)

 

As the name implies, this dataset of 15620 pictures contains diverse interior scenarios that fit into 67 indoor categories to aid in the training of your models.

 

Stores, residences, public areas, places of leisure, and working places are just a few of the categories these Video Datasets fall into, so you’ll have a broad selection of videos to utilize in your projects!

 

Get Database:http://groups.csail.mit.edu/vision/LabelMe/NewVideos/indoorCVPR_09.tar

 

 

  1. Stanford Dogs Datasets(http://vision.stanford.edu/aditya86/VideoNetDogs/) video datasets

 

There are 20,580 pictures and 120 distinct dog breed categories in this collection.

This dataset from Stanford was created using pictures from Video Net and comprises photographs of 120 different dog breeds from across the world. For the goal of fine-grained picture classification, this dataset was created utilizing videos and annotation from Video Net.

 

Get Database:http://vision.stanford.edu/aditya86/VideoNetDogs/videos.tar

 

  1. Labelled Faces In The Wild (http://vis-www.cs.umass.edu/lfw/)

 

This portal offers 13,000 annotated pictures of human faces that you may use in your facial recognition Machine Learning applications.

 

Simply click on the link below to access the dataset. You’ll see a sub-header labeled ‘Download the Database,’ where you may choose which file to download for use in your projects.

 

You won’t have to register or leave your information to access the Video Database, making it super simple to acquire the files you need and start working on your projects!

 

Get Database:http://vis-www.cs.umass.edu/lfw/#download

 

more like this, just click on: https://24x7outsourcing.com/blog/

 

 

  1. Google’s Open Videos (https://storage.googleapis.com/openvideos/web/download.html)

 

A total of 9 million pictures have been tagged with video-level labels and object bounding boxes in this dataset.

Google’s Open Videos: Empowering Accessibility, Innovation, and Collaboration

Introduction: Google’s commitment to openness and innovation extends beyond its search engine and software applications. The company has also made significant contributions to the field of open videos, revolutionizing the way we consume and share video content. Google’s initiatives, such as the development of open video codecs and the creation of platforms like YouTube, have empowered accessibility, fostered innovation, and encouraged collaboration in the digital video landscape. In this article, we will explore the impact of Google’s open videos and the benefits they bring to users and content creators worldwide.

  1. Accessibility for All: One of the key advantages of Google’s open videos is their accessibility. By adopting open video codecs such as VP8 and VP9, Google has made it easier for users to stream and view high-quality video content across different devices and platforms. Open video codecs are not encumbered by restrictive licensing agreements, allowing for broader compatibility and widespread adoption. This accessibility ensures that users, regardless of their device or internet connection, can enjoy seamless video playback and access a diverse range of content.
  2. Innovation and Advancements in Video Compression: Google’s involvement in open videos has spurred innovation and advancements in video compression technologies. The development of VP8 and VP9 codecs has significantly improved video compression efficiency, reducing file sizes without sacrificing visual quality. This has led to faster streaming, reduced bandwidth requirements, and improved user experiences. The advancements in video compression benefit both content creators and consumers by enabling the delivery of high-quality videos over various networks, including mobile and low-bandwidth connections.
  3. Creation of the YouTube Platform: Google’s acquisition of YouTube in 2006 has been a game-changer for online video sharing and content creation. YouTube’s open platform allows anyone to upload, share, and monetize their videos, democratizing content creation and distribution. The platform has provided a space for individuals, artists, educators, and businesses to reach a global audience, express their creativity, and share their knowledge. YouTube’s open nature has fostered a vibrant ecosystem of creators and communities, driving innovation and enabling diverse voices to be heard.
  4. Collaborative Video Production: Google’s open video initiatives have also facilitated collaborative video production. Through YouTube, content creators can collaborate on projects, share resources, and engage with their audience in real-time. The platform offers features such as live streaming, comments, and community engagement, enabling creators to connect with their viewers and build dedicated fan bases. This collaborative aspect has not only empowered content creators but has also enhanced user engagement and the overall viewing experience.
  5. Open Standards and Interoperability: Google’s commitment to open videos extends to promoting open standards and interoperability. Through initiatives like the WebM project, Google advocates for the use of open web technologies to deliver video content seamlessly across different browsers and platforms. Open standards foster a more inclusive and interoperable web ecosystem, reducing fragmentation and enabling developers to build video applications that work consistently across various devices. This emphasis on openness encourages innovation and ensures a better user experience for all.
  6. Support for Creative Commons Licensing: Google’s open video platforms, such as YouTube, provide support for Creative Commons licensing, which enables content creators to share their work under flexible copyright terms. This allows for the easy distribution, remixing, and reuse of videos while respecting the rights and intentions of the creators. Creative Commons licensing fosters a collaborative and participatory culture, encourages creativity, and empowers content creators to control how their work is used and shared.
  7. Educational Resources and Knowledge Sharing: Google’s open video initiatives have also contributed to the accessibility of educational resources and knowledge sharing. YouTube’s educational channels, tutorials, and online courses offer a vast array of learning opportunities for users of all ages and backgrounds. The open nature of YouTube allows educators, institutions, and subject matter experts to share their expertise globally, democratizing education and promoting lifelong learning. Google’s open video platforms have become valuable resources for learners worldwide, providing access to diverse educational content.

Conclusion: Google’s open videos have had a profound impact on the digital video landscape, empowering accessibility, fostering innovation, and encouraging collaboration. Through initiatives like open video codecs, the YouTube platform, support for open standards, and Creative Commons licensing, Google has created a vibrant and inclusive ecosystem for video content creation, sharing, and consumption. The accessibility and openness of Google’s video platforms have empowered users, content creators, educators, and businesses to express their creativity, share their knowledge, and connect with global audiences. As Google continues to drive advancements in open video technologies, the future of digital video looks promising, promising a world where video content is universally accessible, innovative, and collaborative.

Google’s Open Videos: Empowering Accessibility, Innovation, and Collaboration

Introduction: Google’s commitment to openness and innovation extends beyond its search engine and software applications. The company has also made significant contributions to the field of open videos, revolutionizing the way we consume and share video content. Google’s initiatives, such as the development of open video codecs and the creation of platforms like YouTube, have empowered accessibility, fostered innovation, and encouraged collaboration in the digital video landscape. In this article, we will explore the impact of Google’s open videos and the benefits they bring to users and content creators worldwide.

  1. Accessibility for All: One of the key advantages of Google’s open videos is their accessibility. By adopting open video codecs such as VP8 and VP9, Google has made it easier for users to stream and view high-quality video content across different devices and platforms. Open video codecs are not encumbered by restrictive licensing agreements, allowing for broader compatibility and widespread adoption. This accessibility ensures that users, regardless of their device or internet connection, can enjoy seamless video playback and access a diverse range of content.
  2. Innovation and Advancements in Video Compression: Google’s involvement in open videos has spurred innovation and advancements in video compression technologies. The development of VP8 and VP9 codecs has significantly improved video compression efficiency, reducing file sizes without sacrificing visual quality. This has led to faster streaming, reduced bandwidth requirements, and improved user experiences. The advancements in video compression benefit both content creators and consumers by enabling the delivery of high-quality videos over various networks, including mobile and low-bandwidth connections.
  3. Creation of the YouTube Platform: Google’s acquisition of YouTube in 2006 has been a game-changer for online video sharing and content creation. YouTube’s open platform allows anyone to upload, share, and monetize their videos, democratizing content creation and distribution. The platform has provided a space for individuals, artists, educators, and businesses to reach a global audience, express their creativity, and share their knowledge. YouTube’s open nature has fostered a vibrant ecosystem of creators and communities, driving innovation and enabling diverse voices to be heard.
  4. Collaborative Video Production: Google’s open video initiatives have also facilitated collaborative video production. Through YouTube, content creators can collaborate on projects, share resources, and engage with their audience in real-time. The platform offers features such as live streaming, comments, and community engagement, enabling creators to connect with their viewers and build dedicated fan bases. This collaborative aspect has not only empowered content creators but has also enhanced user engagement and the overall viewing experience.
  5. Open Standards and Interoperability: Google’s commitment to open videos extends to promoting open standards and interoperability. Through initiatives like the WebM project, Google advocates for the use of open web technologies to deliver video content seamlessly across different browsers and platforms. Open standards foster a more inclusive and interoperable web ecosystem, reducing fragmentation and enabling developers to build video applications that work consistently across various devices. This emphasis on openness encourages innovation and ensures a better user experience for all.
  6. Support for Creative Commons Licensing: Google’s open video platforms, such as YouTube, provide support for Creative Commons licensing, which enables content creators to share their work under flexible copyright terms. This allows for the easy distribution, remixing, and reuse of videos while respecting the rights and intentions of the creators. Creative Commons licensing fosters a collaborative and participatory culture, encourages creativity, and empowers content creators to control how their work is used and shared.
  7. Educational Resources and Knowledge Sharing: Google’s open video initiatives have also contributed to the accessibility of educational resources and knowledge sharing. YouTube’s educational channels, tutorials, and online courses offer a vast array of learning opportunities for users of all ages and backgrounds. The open nature of YouTube allows educators, institutions, and subject matter experts to share their expertise globally, democratizing education and promoting lifelong learning. Google’s open video platforms have become valuable resources for learners worldwide, providing access to diverse educational content.

Conclusion: Google’s open videos have had a profound impact on the digital video landscape, empowering accessibility, fostering innovation, and encouraging collaboration. Through initiatives like open video codecs, the YouTube platform, support for open standards, and Creative Commons licensing, Google has created a vibrant and inclusive ecosystem for video content creation, sharing, and consumption. The accessibility and openness of Google’s video platforms have empowered users, content creators, educators, and businesses to express their creativity, share their knowledge, and connect with global audiences. As Google continues to drive advancements in open video technologies, the future of digital video looks promising, promising a world where video content is universally accessible, innovative, and collaborative.

V4’s training set includes 14.6 million bounding boxes for 600 item types on 1.74 million pictures, making it the world’s biggest dataset containing object position annotations.

 

Fortunately, you won’t need to register or provide any personal information to access the dataset, allowing you to download it immediately from the website.

 

Get Database:https://storage.googleapis.com/openvideos/web/download.html

 

  1. Visual Genome (http://visualgenome.org/)

 

This dataset gateway is a comprehensive visual knowledge base with captions for 108,077 Video Datasets ranging from people to buildings to signs and everything in between.

 

The following features are described on the website:video datasets

  • 108,077 Photographs
  • 5.4 MILLION DESCRIPTIONS OF REGIONS
  • 1.7 MILLION ANSWERS TO VISUAL QUESTIONS
  • 3.8 Million Instances of Objects
  • There are 2.8 million attributes in the database.
  • There are 2.3 million relationships in the world.

 

To get the datasets provided, you do not need to leave any information or register; simply click the link below to visit the website and download the objects, relationships, and aliases you require.video datasets

 

Get Database:http://visualgenome.org/api/v0/api_home.html

 

  1. COIL100video datasets  (http://www1.cs.columbia.edu/CAVE/software/softlib/coil-100.php)

 

The Columbia University Video Library collection contains 100 distinct things that have been photographed from every angle in a 360° rotation, ranging from toys to personal care items to tablets.video datasets

 

To get the dataset, you don’t need to register or provide any information on the website, making it a simple procedure. Simply click the link below to get the dataset in its entirety.video datasets

 

Get Database:http://www.cs.columbia.edu/CAVE/databases/SLAM_coil-20_coil-100/coil-100/coil-100.zip

 

 

  1. MS COCO (http://mscoco.org/)

 

COCO is a large-scale dataset for detecting, segmenting, and labeling objects in context.video datasets

 

The dataset, as its name implies, comprises a wide range of everyday items that we see in our daily lives, making it suitable for training Machine Learning models.video datasets

 

The following aspects of the Video Datasets are described on the website:

  • Segmentation of objects
  • In-context recognition
  • Segmentation of super pixel items
  • 330K pictures (>200K of which are labelled)
  • 1.5 million instances of objects
  • There are 80 different kinds of items to choose from.
  • There are 91 different types of things.
  • There are five captions per picture.
  • 250,000 persons with important informationvideo datasets

 

You will not be required to register or provide any personal information in order to access the dataset. You may either visit this page or use the links below to download them directly.video datasets

video datasets

Get Database:http://videos.cocodataset.org/zips/train2014.zip

 

 

 

 

 

 

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