Blenderproc

## Overview

Blenderproc is a dataset for object detection tasks - it contains Conector Tapa annotations for 230 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Test Blender Synth Data

## Overview

Test Blender Synth Data is a dataset for object detection tasks - it contains Geometric Shape annotations for 329 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

MixInstruct

  Introduction

This is the official realease of dataset MixInstruct for project LLM-Blender. This dataset contains 11 responses from the current popular instruction following-LLMs that includes:

Stanford Alpaca FastChat Vicuna Dolly V2 StableLM Open Assistant Koala Baize Flan-T5 ChatGLM MOSS Moasic MPT

We evaluate each response with auto metrics including BLEU, ROUGE, BERTScore, BARTScore. And provide pairwise comparison results by prompting ChatGPT for the… See the full description on the dataset page: https://huggingface.co/datasets/llm-blender/mix-instruct.

The MatSim Dataset and benchmark

Lastest version

Synthetic dataset and real images benchmark for visual similarity recognition of materials and textures.

MatSim: a synthetic dataset, a benchmark, and a method for computer vision-based recognition of similarities and transitions between materials and textures focusing on identifying any material under any conditions using one or a few examples (one-shot learning).

Based on the paper: One-shot recognition of any material anywhere using contrastive learning with physics-based rendering

Benchmark_MATSIM.zip: contain the benchmark made of real-world images as described in the paper

MatSim_object_train_split_1,2,3.zip: Contain a subset of the synthetics dataset for images of CGI images materials on random objects as described in the paper.

MatSim_Vessels_Train_1,2,3.zip : Contain a subset of the synthetics dataset for images of CGI images materials inside transparent containers as described in the paper.

*Note: these are subsets of the dataset; the full dataset can be found at:
https://e1.pcloud.link/publink/show?code=kZIiSQZCYU5M4HOvnQykql9jxF4h0KiC5MX

or
https://icedrive.net/s/A13FWzZ8V2aP9T4ufGQ1N3fBZxDF

Code:

Up to date code for generating the dataset, reading and evaluation and trained nets can be found in this URL:https://github.com/sagieppel/MatSim-Dataset-Generator-Scripts-And-Neural-net

Dataset Generation Scripts.zip: Contain the Blender (3.1) Python scripts used for generating the dataset, this code might be odl up to date code can be found here
Net_Code_And_Trained_Model.zip: Contain a reference neural net code, including loaders, trained models, and evaluators scripts that can be used to read and train with the synthetic dataset or test the model with the benchmark. Note code in the ZIP file is not up to date and contains some bugs For the Latest version of this code see this URL

Further documentation can be found inside the zip files or in the paper.

3DHBD 3D Humanix Blender Dataset for Student pose detection applications.

1.PUBLICATION<

2024 3DHBD: Synthetic 3D Dataset for Advanced Student Behavior Analysis in Educational Environments

Journal: Balochistan Journal of Engineering & Applied Sciences (BJEAS)

Status: Published [Paper Link]

2.PUBLICATION<

2024

Advanced Student Behavior Analysis Using Dual-Model Approach for Pose and Emotion Detection

Journal: Multimedia Tools and Applications by Springer

Status: Under review

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12492341%2F4b1386e616cde951af00ae0fa5311b61%2Fc1_normal1.png?generation=1715518170668594&alt=media" alt="">

Overview: 3DHBD (3D Humanix Blender Dataset) is a high-quality synthetic dataset developed using Blender, an open-source and freely accessible software. Due to privacy and security concerns surrounding student data, suitable datasets for student pose detection are scarce. 3DHBD addresses this gap by providing a comprehensive dataset aimed at detection of abnormal behaviour of students in crowded educational environments.

Author Introduction: This dataset was created to fulfill the thesis requirements for a master's degree. This project was created by Hamza Iqbal, [ Linkedin, Github ] who completed his Master's Degree in Electrical Engineering (Signal & Image Processing) from the prestigious Institute of Space Technology (IST), Islamabad, Pakistan in July 2024. Hamza previously holds Bachelor's Degree in Electrical Engineering (Electronics) from Bahria University, Islamabad.

He worked under the supervision of Dr. Madiha Tahir, an Assistant Professor at IST. Dr. Madiha’s research interests lie in the image processing and machine learning domains. [Google Scholar ID]

Key Features of the Dataset: 1. Synthetic Generation: All data is synthetic, ensuring that no actual student information is used. This maintains the dataset's privacy and security integrity. 2. Blender-Based: Created with Blender, an open-source software, it guarantees flexibility for researchers and is freely accessible. 3. High-Quality Labels: Precise labeling of student poses ensures reliable and consistent data for training and testing. 4. Diverse Poses: The dataset contains a diverse range of student poses, enabling more robust model training for pose detection. 5. Educational Context: The dataset is specifically curated for educational settings, making it highly relevant for researchers focused on classroom behavior analysis. 6. Robust Supervision: The dataset was developed under the guidance of an experienced faculty member, ensuring high academic standards and data quality.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12492341%2F4944c3b1864cf469e8b156bce39029ff%2Fist.png?generation=1720936700302708&alt=media" alt="">