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Github Top Repositories
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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.
Mostrar más📈 Análisis del canal de Telegram Github Top Repositories
El canal Github Top Repositories (@githubre) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 330 suscriptores, ocupando la posición 15 272 en la categoría Educación y el puesto 32 126 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 330 suscriptores.
Según los últimos datos del 15 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 413, y en las últimas 24 horas de 8, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.07%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 0.79% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 143 visualizaciones. En el primer día suele acumular 105 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 1.
- Intereses temáticos: El contenido se centra en temas clave como repository, fork, programming, statistic, description.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Top GitHub repositories in one place 🚀
Explore the best projects in programming, AI, data science, and more.”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 16 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Educación.
13 330
Suscriptores
+824 horas
+927 días
+41330 días
Archivo de publicaciones
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✅ "DENSE_REGION_CAPTION" Feature:
This feature generates rich textual descriptions for different regions of the image.
In the video, it introduced excessive glittery effects.
📌 It’s better suited for single-frame usage rather than processing a sequence of video frames.
✅ "REFERRING_EXPRESSION_SEGMENTATION" Feature:
This feature segments areas of the image using expressions referring to them.
However, ⏱️ it is time-consuming, and in terms of accuracy and efficiency, the SAM (Segment Anything Model) performs slightly better than Florence-2.
📓 Notebook:
🔗 https://github.com/ultralytics/notebooks/blob/main/notebooks/how-to-use-florence-2-for-object-detection-image-captioning-ocr-and-segmentation.ipynb
🔍 By: https://t.me/DataScienceN5
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🧠 Inference using Microsoft Florence-2 with the Ultralytics Python Package 😍
✅ Object Detection:
The model performs exceptionally well in detecting various objects and demonstrates impressive zero-shot capabilities. This means it can identify objects without needing specific training on a particular dataset.
🔹 Use case: It is highly suitable for auto-annotating datasets in object detection format.
✅ Accuracy:
The model performs well in terms of accuracy,
but 🔺 it requires significant processing time, making it unsuitable for real-time applications.
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Ready for the most powerful foundation model for medical images/videos?
🚨 Just dropped: MedSAM2
The next-gen foundation model for 3D medical image & video segmentation — built on top of SAM 2.1.
Why it matters:
• Trained on 455K+ 3D image–mask pairs & 76K+ annotated video frames
• >85% reduction in human annotation costs (validated in 3 studies)
• Fast, accurate, and generalizes across organs, modalities, and pathologies
Big impact:
We used MedSAM2 to create 3 massive datasets:
• 5,000 CT lesions
• 3,984 liver MRI lesions
• 251,550 echo video frames
Plug & play:
Deployable in:
→ 3D Slicer
→ JupyterLab
→ Gradio
→ Google Colab
🔖 Project site: https://medsam2.github.io/
🔗 Paper: https://lnkd.in/gbXu6D64
🔍 By: https://t.me/DataScienceN
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Cupcake Counting Project on the Production Line Using Ultralytics YOLO 🧁
🚀 With the rapid growth of the computer vision market in the bakery industry—projected to reach $23.42 billion by 2025—the practical applications of this technology are receiving increasing attention. One of the most important and common applications is the automated counting of bakery products on production lines.
In this project, the development team provided a model for cupcake detection, and Ultralytics solutions were used to implement the counting process. The only necessary step for deployment was updating the region coordinates for detection, which was successfully accomplished.
Advantages:
✅ Instantly detects and counts cupcakes as they move.
✅ Handles high-speed conveyor belt production effortlessly.
🔗 Complete code ➡️https://lnkd.in/d-4Zk2Q5
🔍 By: https://t.me/DataScienceN
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😍😍😍😍😍😍😍😍
It’s truly fascinating — definitely worth diving deeper into and working on!
😍😍😍😍😍😍😍😍
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🔖 ImageBind: One Embedding Space To Bind Them All
📝 This project is a significant step forward in understanding and connecting information from diverse sources like images, text, audio, video, and even motion sensor data.
⚙️ Supports 6 Modalities:
📷 Image
📝 Text
🔈 Audi
🎥 Video
🦴 IMU sensor data (e.g., accelerometer)
🙄 Depth/Thermal & 3D data
Interestingly, only some modalities had labels, yet ImageBind learned to align them through self-supervised learning.
💫 Key Features:
..No need for paired data (e.g., images and audio don’t have to be aligned)..Leverages contrastive learning for learning joint embedding space
..Competes with CLIP and AudioCLIP, but with better accuracy and coverage..Enables zero-shot retrieval (e.g., finding relevant video using just a sentence)
📌 Repo: https://github.com/facebookresearch/ImageBind
🔍 By: https://t.me/DataScienceN 🌟
#ImageBind #MultimodalAI #MetaAI #DeepLearning #SelfSupervised
13 332
The latest and the most up-to-date cyber news will be presented on PPHM HACKER NEWS.
PPHM subscribers are the first people that receive firsthand cybernews and Tech news.
You won't miss any cyber news with us.
https://t.me/pphm_HackerNews
13 332
🔖 Project name : Analysis of Covid-19 chest x-rays
📝 In order to diagnose patients with Covid-19, the analysis of chest X-rays is a possibility to be explored to more easily detect positive cases. If the classification through deep learning of such data proves effective in detecting positive cases, then this method can be used in hospitals and clinics when traditional testing cannot be done.
📌 Repo:
https://github.com/rehabaam/ds_covid19_project
🔍 By: https://t.me/DataScienceN 🌟
13 332
📌 Project name: Cat/Dog/Fox Lightning 2024
By: https://t.me/DataScienceN 🌟13 332
📌 Project name: Cat/Dog/Fox Lightning 2024
📝 Language: #Python
🔗 Dataset Link: https://www.kaggle.com/datasets/snmahsa/animal-image-dataset-cats-dogs-and-foxes
🖋 Download the dataset offline:
https://t.me/datasets1/668
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This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/codeprogrammer
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I advise you to use this bot, the bot has a strong launch and I guarantee you at least 200 dollars when Airdrop. In addition, you will get free daily money whenever you invite more friends
https://t.me/donot/game?startapp=418788114
The bot is quite similar to the Dogs bot and Paws
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Repost from AI & ML Papers
Coursera has launched a collaboration with the Stars platform to enable students to self-fund using the Stars platform.
Students can now access free Coursera scholarships through Stars.
Don't miss the opportunity: Click here.
13 332
Pandas Cookbook (2025)
Link Download: https://best-links.org/s?468c1ea5
How to Download Books (Read it, important)
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (2023)
Link Download: https://best-links.org/s?6eed180f
How to Download Books (Read it, important)
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We will only send books with very high rating here.
Sending books directly here would be risky so we will encrypt the book download mechanism using the (content lock) mechanism.
The first and most important step is that you must open the link using Chrome or any other browser other than the default Telegram browser to ensure that the content is successfully unlocked.
In the pictures attached to the post, there is a way to unlock the content and download the book successfully. The mechanism may seem vague to you at first, but with time and repetition, you will adapt to this mechanism.
We do this and give things away for free only to people who deserve it.
