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reacted to their post with 🔥 2 days ago
🙋‍♀️ Happy Monday! Duality AI has released another dataset for pose estimation https://huggingface.co/datasets/duality-robotics/pose_estimation5.1 It's once again 100% ✨FREE✨ Access the full-size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/pose-colab?sidebarMode=learn Or check it out in the linked HuggingFace dataset Why train a model in pose estimation? Many functions require pose estimation, such as... 🤖Defining the orientation of an object on a conveyer belt for pick and place operations with a robotic arm, 🤖 Replicating an object's pose for AR and VR application overlays, 🤖 Localizing and mapping an environment for path navigation, 🤖 ...and more! What makes this dataset useful for training a model? 💠Duality AI's digital twins are not generated by AI, but are instead crafted by 3D artists. This allows the training from this data to transfer into real-world applicability. Read more about our techniques for bridging the Sim2Real gap here: https://www.duality.ai/blog/ml-synthetic-data-model 💠The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more using a versatile python API 💠FalconEditor is able to create 100% accurate labels at the SAME TIME as it creates the images. This makes collecting data for tasks such pose-estimation easier, faster, and more reliable. Interested in a specific dataset? Let us know! We're always looking for new ideas on what datasets to create next 👀
reacted to their post with 🤗 2 days ago
🙋‍♀️ Happy Monday! Duality AI has released another dataset for pose estimation https://huggingface.co/datasets/duality-robotics/pose_estimation5.1 It's once again 100% ✨FREE✨ Access the full-size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/pose-colab?sidebarMode=learn Or check it out in the linked HuggingFace dataset Why train a model in pose estimation? Many functions require pose estimation, such as... 🤖Defining the orientation of an object on a conveyer belt for pick and place operations with a robotic arm, 🤖 Replicating an object's pose for AR and VR application overlays, 🤖 Localizing and mapping an environment for path navigation, 🤖 ...and more! What makes this dataset useful for training a model? 💠Duality AI's digital twins are not generated by AI, but are instead crafted by 3D artists. This allows the training from this data to transfer into real-world applicability. Read more about our techniques for bridging the Sim2Real gap here: https://www.duality.ai/blog/ml-synthetic-data-model 💠The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more using a versatile python API 💠FalconEditor is able to create 100% accurate labels at the SAME TIME as it creates the images. This makes collecting data for tasks such pose-estimation easier, faster, and more reliable. Interested in a specific dataset? Let us know! We're always looking for new ideas on what datasets to create next 👀
reacted to their post with 😎 2 days ago
🙋‍♀️ Happy Monday! Duality AI has released another dataset for pose estimation https://huggingface.co/datasets/duality-robotics/pose_estimation5.1 It's once again 100% ✨FREE✨ Access the full-size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/pose-colab?sidebarMode=learn Or check it out in the linked HuggingFace dataset Why train a model in pose estimation? Many functions require pose estimation, such as... 🤖Defining the orientation of an object on a conveyer belt for pick and place operations with a robotic arm, 🤖 Replicating an object's pose for AR and VR application overlays, 🤖 Localizing and mapping an environment for path navigation, 🤖 ...and more! What makes this dataset useful for training a model? 💠Duality AI's digital twins are not generated by AI, but are instead crafted by 3D artists. This allows the training from this data to transfer into real-world applicability. Read more about our techniques for bridging the Sim2Real gap here: https://www.duality.ai/blog/ml-synthetic-data-model 💠The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more using a versatile python API 💠FalconEditor is able to create 100% accurate labels at the SAME TIME as it creates the images. This makes collecting data for tasks such pose-estimation easier, faster, and more reliable. Interested in a specific dataset? Let us know! We're always looking for new ideas on what datasets to create next 👀
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reacted to their post with 🔥🤗😎 2 days ago
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1475
🙋‍♀️ Happy Monday! Duality AI has released another dataset for pose estimation

duality-robotics/pose_estimation5.1

It's once again 100% ✨FREE✨
Access the full-size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/pose-colab?sidebarMode=learn
Or check it out in the linked HuggingFace dataset

Why train a model in pose estimation?
Many functions require pose estimation, such as...
🤖Defining the orientation of an object on a conveyer belt for pick and place operations with a robotic arm,
🤖 Replicating an object's pose for AR and VR application overlays,
🤖 Localizing and mapping an environment for path navigation,
🤖 ...and more!

What makes this dataset useful for training a model?

💠Duality AI's digital twins are not generated by AI, but are instead crafted by 3D artists. This allows the training from this data to transfer into real-world applicability. Read more about our techniques for bridging the Sim2Real gap here: https://www.duality.ai/blog/ml-synthetic-data-model
💠The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more using a versatile python API
💠FalconEditor is able to create 100% accurate labels at the SAME TIME as it creates the images. This makes collecting data for tasks such pose-estimation easier, faster, and more reliable.

Interested in a specific dataset? Let us know!
We're always looking for new ideas on what datasets to create next 👀
posted an update 3 days ago
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Post
1475
🙋‍♀️ Happy Monday! Duality AI has released another dataset for pose estimation

duality-robotics/pose_estimation5.1

It's once again 100% ✨FREE✨
Access the full-size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/pose-colab?sidebarMode=learn
Or check it out in the linked HuggingFace dataset

Why train a model in pose estimation?
Many functions require pose estimation, such as...
🤖Defining the orientation of an object on a conveyer belt for pick and place operations with a robotic arm,
🤖 Replicating an object's pose for AR and VR application overlays,
🤖 Localizing and mapping an environment for path navigation,
🤖 ...and more!

What makes this dataset useful for training a model?

💠Duality AI's digital twins are not generated by AI, but are instead crafted by 3D artists. This allows the training from this data to transfer into real-world applicability. Read more about our techniques for bridging the Sim2Real gap here: https://www.duality.ai/blog/ml-synthetic-data-model
💠The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more using a versatile python API
💠FalconEditor is able to create 100% accurate labels at the SAME TIME as it creates the images. This makes collecting data for tasks such pose-estimation easier, faster, and more reliable.

Interested in a specific dataset? Let us know!
We're always looking for new ideas on what datasets to create next 👀
liked a dataset 4 days ago
updated 2 datasets 6 days ago
liked a dataset 6 days ago
reacted to their post with 🤗🤯😎🔥 6 days ago
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🚀 Duality is super excited to announce that our Kaggle competition is LIVE! Synthetic-to-Real Object Detection Challenge is LIVE! 🚦
Want to master AI training, learn industry-proven synthetic data workflows, and compete for public recognition and cash prizes?

👉 Join our Synthetic-to-Real Object Detection Challenge on Kaggle! https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview

Compete to build the top-performing model capable of detecting real-world objects—trained entirely on synthetic data. Master these industry-proven methods for faster, more targeted, and diverse dataset creation, and set yourself apart, unlocking today's most exciting AI opportunities.

Ready to test your skills?

🏆 The Challenge

Train an object detection model using synthetic images created with Falcon—Duality AI's cutting-edge digital twin simulation software—then evaluate your model on real-world imagery.

The Twist?
📈 Boost your model’s accuracy by creating and refining your own custom synthetic datasets using Falcon! Get access to the tools and double the data by following this link and creating a free account-
https://falcon.duality.ai/secure/documentation/ex-1-objdetection?sidebarMode=learn

Win Cash Prizes & Recognition
🔹 Earn cash and public shout-outs from the Duality AI accounts
Enhance Your Portfolio
🔹 Demonstrate your real-world AI and ML expertise in object detection to prospective employers and collaborators.
Expand Your Network
🔹 Engage, compete, and collaborate with fellow ML engineers, researchers, and students.

🚀 Put your skills to the test and join our Kaggle competition today: https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview
posted an update 6 days ago
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Post
2795
🚀 Duality is super excited to announce that our Kaggle competition is LIVE! Synthetic-to-Real Object Detection Challenge is LIVE! 🚦
Want to master AI training, learn industry-proven synthetic data workflows, and compete for public recognition and cash prizes?

👉 Join our Synthetic-to-Real Object Detection Challenge on Kaggle! https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview

Compete to build the top-performing model capable of detecting real-world objects—trained entirely on synthetic data. Master these industry-proven methods for faster, more targeted, and diverse dataset creation, and set yourself apart, unlocking today's most exciting AI opportunities.

Ready to test your skills?

🏆 The Challenge

Train an object detection model using synthetic images created with Falcon—Duality AI's cutting-edge digital twin simulation software—then evaluate your model on real-world imagery.

The Twist?
📈 Boost your model’s accuracy by creating and refining your own custom synthetic datasets using Falcon! Get access to the tools and double the data by following this link and creating a free account-
https://falcon.duality.ai/secure/documentation/ex-1-objdetection?sidebarMode=learn

Win Cash Prizes & Recognition
🔹 Earn cash and public shout-outs from the Duality AI accounts
Enhance Your Portfolio
🔹 Demonstrate your real-world AI and ML expertise in object detection to prospective employers and collaborators.
Expand Your Network
🔹 Engage, compete, and collaborate with fellow ML engineers, researchers, and students.

🚀 Put your skills to the test and join our Kaggle competition today: https://www.kaggle.com/competitions/synthetic-2-real-object-detection-challenge/overview
published a dataset 7 days ago
updated a dataset 7 days ago
reacted to their post with 👍🔥🚀🧠 9 days ago
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3187
Duality.ai just released a 1000 image dataset used to train a YOLOv8 model in multiclass object detection -- and it's 100% free!
duality-robotics/YOLOv8-Multiclass-Object-Detection-Dataset

Access the full size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/ex3-dataset?sidebarMode=learn

Or check it out in the linked HuggingFace dataset!

What makes this dataset unique, useful, and capable of bridging the Sim2Real gap?

💠 The digital twins are not generated by AI, but instead crafted by 3D artists to be INDISTINGUISHABLE from the physical-world objects. This allows the training from this data to transfer into real-world applicability

💠 The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more. This enables robust model training.

💠 The labels are created along with the data. This not only saves large amounts of time, but also ensures the labels are incredibly accurate and reliable.

This HuggingFace dataset is a 20 image and label sample, but you can get the rest at no cost by creating a FalconCloud account here: https://falcon.duality.ai/secure/documentation/ex3-dataset?sidebarMode=learn.

Once you verify your email, the link will redirect you to the dataset page.
posted an update 9 days ago
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3187
Duality.ai just released a 1000 image dataset used to train a YOLOv8 model in multiclass object detection -- and it's 100% free!
duality-robotics/YOLOv8-Multiclass-Object-Detection-Dataset

Access the full size dataset by creating an EDU account here- https://falcon.duality.ai/secure/documentation/ex3-dataset?sidebarMode=learn

Or check it out in the linked HuggingFace dataset!

What makes this dataset unique, useful, and capable of bridging the Sim2Real gap?

💠 The digital twins are not generated by AI, but instead crafted by 3D artists to be INDISTINGUISHABLE from the physical-world objects. This allows the training from this data to transfer into real-world applicability

💠 The simulation software, called FalconEditor, can easily create thousands of images with varying lighting, posing, occlusions, backgrounds, camera positions, and more. This enables robust model training.

💠 The labels are created along with the data. This not only saves large amounts of time, but also ensures the labels are incredibly accurate and reliable.

This HuggingFace dataset is a 20 image and label sample, but you can get the rest at no cost by creating a FalconCloud account here: https://falcon.duality.ai/secure/documentation/ex3-dataset?sidebarMode=learn.

Once you verify your email, the link will redirect you to the dataset page.