Computer Science and Programming
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Channel specialized for advanced topics of:
* Artificial intelligence,
* Machine Learning,
* Deep Learning,
* Computer Vision,
* Data Science
* Python

Admin: @otchebuch

Memes: @memes_programming

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GLIGEN: Open-Set Grounded Text-to-Image Generation.

GLIGEN
(Grounded-Language-to-Image Generation) a novel approach that builds upon and extends the functionality of existing pre-trained text-to-image diffusion models by enabling them to also be conditioned on grounding inputs.

Project page:
https://gligen.github.io/

Paper:
https://arxiv.org/abs/2301.07093

Github (coming soon):
https://github.com/gligen/GLIGEN

Demo:
https://huggingface.co/spaces/gligen/demo


๐Ÿ‘‰@computer_science_and_programming
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Cut and Learn for Unsupervised Object Detection and Instance Segmentation

Cut-and-LEaRn
(CutLER) is a simple approach for training object detection and instance segmentation models without human annotations. It outperforms previous SOTA by 2.7 times for AP50 and 2.6 times for AR on 11 benchmarks.

Paper:
https://arxiv.org/pdf/2301.11320.pdf

Github:
https://github.com/facebookresearch/CutLER

Demo:
https://colab.research.google.com/drive/1NgEyFHvOfuA2MZZnfNPWg1w5gSr3HOBb?usp=sharing

๐Ÿ‘‰@computer_science_and_programming
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Gen-1: The Next Step Forward for Generative AI

Use words and images to generate new videos out of existing

Introducing Gen-1: a new AI model that uses language and images to generate new videos out of existing ones.

https://research.runwayml.com/gen1

โญ๏ธ Project:
https://research.runwayml.com/gen1

โœ… Paper:
https://arxiv.org/abs/2302.03011

๐Ÿ“ŒRequest form:
https://docs.google.com/forms/d/e/1FAIpQLSfU0O_i1dym30hEI33teAvCRQ1i8UrGgXd4BPrvBWaOnDgs9g/viewform

๐Ÿ‘‰@computer_science_and_programming
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YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection

SPATIO-temporal action detection (STAD) aims to detect action instances in the current frame, which it has been widely applied, such as video surveillance and somatosensory game.

Paper:
https://arxiv.org/pdf/2302.06848.pdf

Github:
https://github.com/yjh0410/YOWOv2

Dataset:
https://drive.google.com/file/d/1Dwh90pRi7uGkH5qLRjQIFiEmMJrAog5J/view?usp=sharing

๐Ÿ‘‰@computer_science_and_programming
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3D-aware Conditional Image Synthesis (pix2pix3D)

Pix2pix3D
synthesizes 3D objects (neural fields) given a 2D label map, such as a segmentation or edge map

Github:
https://github.com/dunbar12138/pix2pix3D

Paper:
https://arxiv.org/abs/2302.08509

Project:
https://www.cs.cmu.edu/~pix2pix3D/

Datasets:
CelebAMask , AFHQ-Cat-Seg , Shapenet-Car-Edge


๐Ÿ‘‰@computer_science_and_programming
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Efficient Teacher: Semi-Supervised Object Detection for YOLOv5

โœ… Efficient Teacher introduces semi-supervised object detection into practical applications, enabling users to obtain a strong generalization capability with only a small amount of labeled data and large amount of unlabeled data.

โœ… Efficient Teacher provides category and custom uniform sampling, which can quickly improve the network performance in actual business scenarios.


Paper:
https://arxiv.org/abs/2302.07577

Github:
https://github.com/AlibabaResearch/efficientteacher

๐Ÿ‘‰@computer_science_and_programming
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Multivariate Probabilistic Time Series Forecasting with Informer

Efficient transformer-based model for LSTF.

Method introduces a Probabilistic Attention mechanism to select the โ€œactiveโ€ queries rather than the โ€œlazyโ€ queries and provides a sparse Transformer thus mitigating the quadratic compute and memory requirements of vanilla attention.

๐Ÿค—Hugging face:
https://huggingface.co/blog/informer

โฉ Paper:
https://huggingface.co/docs/transformers/main/en/model_doc/informer

โญ๏ธ Colab:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multivariate_informer.ipynb

๐Ÿ’จ Dataset:
https://huggingface.co/docs/datasets/v2.7.0/en/package_reference/main_classes#datasets.Dataset.set_transform

๐Ÿ‘‰@computer_science_and_programming
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ViperGPT: Visual Inference via Python Execution for Reasoning

ViperGPT,
a framework that leverages code-generation models to compose vision-and-language models into subroutines to produce a result for any query.


Github:
https://github.com/cvlab-columbia/viper

Paper:
https://arxiv.org/pdf/2303.08128.pdf

Project:
https://paperswithcode.com/dataset/beat

๐Ÿ‘‰@computer_science_and_programming
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Test of Time: Instilling Video-Language Models with a Sense of Time

GPT-5 will likely have video abilities, but will it have a sense of time? Here is answer to this question in #CVPR2023 paper by student of University of Amsterdam to learn how to instil time into video-language foundation models.

Paper:
https://arxiv.org/abs/2301.02074

Code:
https://github.com/bpiyush/TestOfTime

Project Page:
https://bpiyush.github.io/testoftime-website/

๐Ÿ‘‰ @computer_science_and_programming
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DragGAN.gif
20.6 MB
Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

Paper:
https://arxiv.org/abs/2305.10973

Github:
https://github.com/XingangPan/DragGAN

Project page:
https://vcai.mpi-inf.mpg.de/projects/DragGAN/

๐Ÿ‘‰ @computer_science_and_programming
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๐Ÿ”ญ GRES: Generalized Referring Expression Segmentation

New benchmark (GRES), which extends the classic RES to allow expressions to refer to an arbitrary number of target objects.

๐Ÿ–ฅ Github: https://github.com/henghuiding/ReLA

โฉ Paper: https://arxiv.org/abs/2306.00968

๐Ÿ”Ž Project: https://henghuiding.github.io/GRES/

๐Ÿ“Œ New dataset: https://github.com/henghuiding/gRefCOCO

๐Ÿ‘‰ @computer_science_and_programming
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80+ Jupyter Notebook tutorials on image classification, object detection and image segmentation in various domains
๐Ÿ“Œ Agriculture and Food
๐Ÿ“Œ Medical and Healthcare
๐Ÿ“Œ Satellite
๐Ÿ“Œ Security and Surveillance
๐Ÿ“Œ ADAS and Self Driving Cars
๐Ÿ“Œ Retail and E-Commerce
๐Ÿ“Œ Wildlife

Classification library
https://github.com/Tessellate-Imaging/monk_v1

Notebooks - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo

Detection and Segmentation Library
https://github.com/Tessellate-Imaging/

Monk_Object_Detection
Notebooks: https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo

๐Ÿ‘‰ @computer_science_and_programming
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๐—›๐—ผ๐˜„ ๐˜๐—ผ ๐˜๐—ฒ๐˜€๐˜ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—”๐—ฃ๐—œ๐˜€ ๐—ฑ๐—ถ๐—ฟ๐—ฒ๐—ฐ๐˜๐—น๐˜† ๐—ณ๐—ฟ๐—ผ๐—บ ๐—ฉ๐—ถ๐˜€๐˜‚๐—ฎ๐—น ๐—ฆ๐˜๐˜‚๐—ฑ๐—ถ๐—ผ ๐—–๐—ผ๐—ฑ๐—ฒ?

You can immediately do this from your Visual Studio Code, as Postman just released a VS Code extension that integrates API building and testing into your code editor.

What you can do with the extension:

๐Ÿ”น๐—ฆ๐—ฒ๐—ป๐—ฑ (๐—บ๐˜‚๐—น๐˜๐—ถ๐—ฝ๐—ฟ๐—ผ๐˜๐—ผ๐—ฐ๐—ผ๐—น) ๐—ฟ๐—ฒ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐˜€
๐Ÿ”น๐—ฆ๐—ฒ๐—ป๐—ฑ ๐—ฟ๐—ฒ๐—พ๐˜‚๐—ฒ๐˜€๐˜๐˜€ ๐—ณ๐—ฟ๐—ผ๐—บ ๐˜†๐—ผ๐˜‚๐—ฟ ๐—ต๐—ถ๐˜€๐˜๐—ผ๐—ฟ๐˜†
๐Ÿ”น๐—จ๐˜€๐—ฒ ๐—ฐ๐—ผ๐—น๐—น๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป๐˜€
๐Ÿ”น๐—จ๐˜€๐—ฒ ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜ ๐—ฒ๐—ป๐˜ƒ๐—ถ๐—ฟ๐—ผ๐—ป๐—บ๐—ฒ๐—ป๐˜๐˜€
๐Ÿ”น๐—ฉ๐—ถ๐—ฒ๐˜„ ๐—ฎ๐—ป๐—ฑ ๐—ฒ๐—ฑ๐—ถ๐˜ ๐—ฐ๐—ผ๐—ผ๐—ธ๐—ถ๐—ฒ๐˜€

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Backend Burger ๐Ÿ”
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Wondering how C++, Java, Python Work?

๐Ÿ”ต C++
C++ is like the superhero of programming languages. It's a compiled language, meaning your code is transformed into machine code that your computer can understand before it runs. This compilation process is crucial for efficiency and performance. C++ gives you precise control over memory and hardware, making it a top choice for systems programming and game development. It's like wielding a finely-tuned instrument in the world of code! ๐ŸŽธ๐Ÿ’ป

๐Ÿ”ด Java
Java, on the other hand, is the coffee of programming languages. It's a compiled language too but with a twist. Java code is compiled into bytecode, which runs on the Java Virtual Machine (JVM). This bytecode can run on any platform with a compatible JVM, making Java highly portable and platform-independent. It's a bit like sending your code to a virtual coffee machine that serves it up just the way you like it on any OS! โ˜•๏ธ๐Ÿ’ผ

๐Ÿ Python
Python is the friendly neighborhood programming language. It's an interpreted language, which means there's no compilation step. Python code is executed line by line by the Python interpreter. This simplicity makes it great for beginners and rapid development. Python's extensive library ecosystem and easy syntax make it feel like you're scripting magic spells in a magical world! ๐Ÿช„๐Ÿ

In the end, the choice of programming language depends on your project's needs and your personal preferences. Each language has its strengths and weaknesses, but they all share the goal of bringing your ideas to life through code. ๐Ÿš€๐Ÿ’ก

So, whether you're crafting the perfect C++ masterpiece, brewing up Java applications, or scripting Python magic, remember that programming languages are the tools that empower us to create amazing things in the digital realm. Embrace the language that speaks to you and keep coding! ๐Ÿ’ป๐ŸŒŸ
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What is Kafka?

Kafka is an open-source, distributed event streaming platform that serves as the central nervous system for data in modern enterprises. It's designed to handle real-time data feeds, process them efficiently, and make them available for a variety of applications in real-time.

๐Ÿ›  Use Cases:
- Real-time Analytics
- Log Aggregation
- Event Sourcing
- Data Integration
- Machine Learning Pipelines
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