Saqib Iqbal’s Post

Bringing AI into Video Object Detection! 🎥 I’m thrilled to share my recent project on object detection in video clips using #YOLO and #OpenCV. This work has been a deep dive into real-time video processing, with applications that can drive change in industries like retail, surveillance, and automated content tagging. Here’s a breakdown of the approach I took: 🔍 Key Features: - Leveraged YOLOv5 for detecting and classifying objects in each frame with high accuracy. - Processed video frames in real-time to dynamically display confidence scores for each detected object. - Highlighted objects with bounding boxes and labels for better visual understanding. - Stored and managed the enhanced video using Google Drive, making it easy to scale the approach. Working with this setup, I tested the model on several clips and fine-tuned detection techniques. For a bit of fun, I included clips featuring characters inspired by The Secret Life of Pets—a personal favorite! This hands-on work with AI in video has me inspired to see how far object detection can go in enabling smart solutions. Stay tuned for more updates as I continue building! ✨ #ai #objectdetection #YOLO #computervision #videoprocessing #python #innovation #machinelearning #googlecolab #techprojects

���� Excited to Share My Latest Project: YOLOv8 Object Detection on Video! 🔍🎥 I'm thrilled to announce my latest AI-powered project that enables real-time video object detection using the YOLOv8 model. This Streamlit app allows you to upload videos, detect objects, and download processed videos with bounding boxes around detected objects. 🔗 Live Demo: https://lnkd.in/dwAmzYG7 🔗 GitHub Repository: https://lnkd.in/dxyiUiVC 💡 Key Features: Upload Video: Support for MP4, AVI, and MOV formats. Real-time Object Detection: Detects and highlights objects using the YOLOv8 model. Downloadable Results: Easily download the processed video with the detected objects. This project has been an incredible learning experience, particularly in integrating AI models into practical applications and developing user-friendly interfaces with Streamlit. ✔️ Special Thanks: iCodeGuru Pak Angels ASPIRE Pakistan #TheEngineersPakistan (TEP) Sir Zafar Shahid, PhD Sir Mohammad Anwar Khan Sir Rizwan Ghaffar Madam Maha Zainab Sir Muhammad Danish Iqbal Your guidance has been instrumental in this achievement! 🙏 🚀 I’d love to hear your thoughts and feedback on this project! 💬 #GenerativeAI #Gradio #WhisperModel #GroqAPI #AudioProcessing #AI #Python #MachineLearning #NLP #SpeechSynthesis

🚀 Midjourney Killer is Here! Meet 𝗙𝗟𝗨𝗫.𝟭 from Black Forest Labs! 🚀 Attention, data scientists and AI enthusiasts! Black Forest Labs has just launched something extraordinary—the FLUX.1 suite of models, setting a new gold standard in text-to-image synthesis. 🌟 Why is FLUX.1 a game-changer? It outperforms popular models like Midjourney v6.0 and DALL·E 3 (HD) in visual quality, prompt following, size/aspect variability, typography, and output diversity. Ready to revolutionize your projects? Here’s the lowdown on the FLUX.1 Model Family: 🔹 FLUX.1 [pro]: The pinnacle of performance, delivering top-notch image generation. Available via API, Replicate, and fal.ai. 🔹 FLUX.1 [dev]: Open-weight and guidance-distilled for non-commercial use, offering efficiency and quality on Hugging Face. 🔹 FLUX.1 [schnell]: Blazing fast for local development and personal use, openly available under Apache 2.0 on Hugging Face and GitHub. Black Forest Labs is on a mission to democratize generative AI, making cutting-edge technology accessible to everyone. Their innovations, including VQGAN, Latent Diffusion, and Stable Diffusion, have already made waves in the AI community. Excited to dive in? I’ve created a free Google Colab notebook guide to help you explore these amazing models. Don’t miss out—start experimenting with FLUX.1 today! 📓 https://lnkd.in/g5GeBj2k #GenerativeAI #MidjourneyKiller #AI #TechInnovation #BlackForestLabs #FLUX1 #GoogleColab

Build your personal AI assistant, watch the full tutorial! 🤖💡 During our past live coding workshop, we built an app that uses the Gemini family of AI models to provide personalized furniture recommendations based on uploaded images. 🛋️📸 Additionally, we demonstrated a live example of generating video descriptions and identifying top global locations similar to your uploaded video. 🌍🎥 Learn how to leverage Rockset as a vector database to manage and query large datasets efficiently, and how to use Gemini APIs within your apps. Subscribe to our channel and watch the full workshop—link in comments! 📺 #AI #MachineLearning #Gemini #Rockset #VectorDatabase #LiveCoding #Tutorial #TechWorkshop

🌟 Excited to share my latest project: AI Healthcare Chatbot! 🚀 This chatbot leverages the power of AI to provide instant and accurate responses to healthcare-related queries, such as medication information and general health advice. Built using [specify technologies or frameworks, e.g., Python, Gradio, TensorFlow], this project demonstrates how AI can enhance accessibility and empower users with knowledge. Key features: 💡 Instant health-related Q&A 🛠 User-friendly interface with real-time responsiveness 🌐 Accessible locally and online This is an excellent step toward integrating AI into everyday healthcare solutions, making reliable information available at our fingertips. I’d love to hear your feedback and ideas for further improvements! 🖥 Check out the GitHub repository here: https://lnkd.in/dvuFQnfs Looking forward to connecting with like-minded individuals passionate about AI and healthcare innovation! 💬 #ArtificialIntelligence #HealthcareChatbot #Innovation #TechnologyForGood

Introducing VisionAssist AI Leveraging Google's Gemini-1.5 Flash AI model, I meticulously crafted a Python-powered Streamlit application that does more than just process images – it creates meaningful experiences. The journey involved intricate integration of: ● Google's Generative AI for intelligent image analysis ● gTTS for seamless text-to-speech conversion ● Advanced prompt engineering to generate contextually rich descriptions 🔍 What makes VisionAssist AI unique? ⬭ Advanced scene description using tactile and auditory language ⬭ Intelligent text extraction from images ⬭ Safe navigation guidance powered by AI ⬭ Seamless text-to-speech conversion 🔗 Explore the Project: GitHub: [https://lnkd.in/gsZ4XSrs] Web App: [https://lnkd.in/gZqQbcDt] A huge shoutout to the incredible team and mentors who supported this journey of making technology more inclusive! Special Thanks to: Kanav Bansal Innomatics Research Labs #AI #Accessibility #TechForGood #GenerativeAI #Innovation #ArtificialIntelligence #Accessibility #AIInnovation #AssistiveTechnology #GenerativeAI #MachineLearning #Python #GoogleAI #Streamlit #TechSolution #AIForAll #Innovation #SocialTech #DisabilityInclusion #AIAccessibility #OpenSource #AIForHumanity

Just watched Andrew Ng’s session at Snowflake BUILD, and I'm even more excited about where AI is heading. Ng demoed a tool that lets you segment unstructured data- in this case video footage- into clips that could be analyzed with self-generated and reusable Python code. In the integrated UI, he was able to type in a few keywords and quickly find the exact clips across a catalog of footage that matched- super useful for anyone with loads of video content. This demo reminded me of a recent hackathon I volunteered for, collaborating with a talented team of developers to build an AI-powered multimedia management solution for an NGO with a need to navigate images and videos more easily. We designed a system with bi-directional media syncing, automated image labeling using machine learning, and a keyword-based retrieval feature for efficient image search- but video content still needed to be addressed. Ng's demo was a great example of how more fine-tuned use of AI could transform even video content for organizations with extensive video libraries that need frequent access and analysis. Imagine the impact for news organizations, sports broadcasters, research institutions, educational platforms, historical archives, or even emergency response teams- all of which could instantly access specific clips with a simple search. Ng called AI “the new electricity,” and he’s right- things that used to take months can now be done in days. It’s a crazy time to be working in AI, with tools like this making it easier and faster to put big ideas into action. Try out LandingAI's VisionAgent for free here: https://va.landing.ai/ #Snowflake #SnowflakeBUILD #Build2024 #LandingAI #VisionAgent #AI #GenAI #LLM #AgenticWorkflows #AgenticAI

🚗✨ Exciting Milestone Achieved! 🚀I’m thrilled to share that I’ve successfully completed the second task in my AI and ML journey: developing a car price prediction model! Using powerful tools like NumPy, Pandas, and Scikit-learn, I implemented a Linear Regression model that accurately predicts car prices based on various features. 🎉To enhance the model's performance, I utilized OneHotEncoder for categorical data and evaluated its effectiveness with the R² score. The entire project was developed in PyCharm, and I deployed it using Flask, making it accessible for real-world applications.I’m eager to hear your thoughts on car price prediction and any insights you might have on improving model accuracy ! Let’s connect and discuss! 💬🔍 #AI #MachineLearning #DataScience #CarPricePrediction #Flask #LinearRegression InternPe

E L O N x x A I x G R O K - Elon Musk’s xAI has introduced its first multimodal model. Not only can it understand text, but it’s also capable of processing things seen in documents, diagrams, charts, screenshots and photographs. Grok-1.5 Vision, or Grok-1.5V, will be available soon to early testers and existing Grok users. “Grok-1.5V is competitive with existing frontier multimodal models in a number of domains, ranging from multi-disciplinary reasoning to understanding documents, science diagrams, charts, screenshots, and photographs,” the company said in a blog post. The unveiling comes weeks after xAI revealed its updated chatbot model Grok-1.5. The company highlights seven examples showcasing Grok-1.5V’s potential, from transforming a whiteboard sketch of a flowchart into Python code and generating a bedtime story simply from a kid’s drawing to explaining a meme, converting a table into a CSV file format and identifying if your deck has rotten wood and needs replacing. Check it out: https://lnkd.in/gtf3GDpQ #wakupimagine #elonmusk #grok #ai #genai #aiimaginelabs

🌟 Excited to Share My Latest Project: Object Detection Using YOLOv5! 🌟 I am thrilled to announce the completion of my project, where I implemented the YOLOv5 object detection model. This project aims to detect and classify objects in images with remarkable accuracy, leveraging the power of deep learning and computer vision. 🔍 Project Overview: Model Used: YOLOv5, pre-trained on the COCO dataset. Dataset: COCO dataset, consisting of 80 diverse object categories, including vehicles, animals, household items, and much more. 💻 Key Features: Detects objects in real-time images. Processes various object categories, ensuring high accuracy and efficiency. 📈 Results: The model has demonstrated impressive performance in detecting objects, showcasing its potential for various applications in industries like security, automotive, and retail. 🚀 Explore the Project: Check out the GitHub repository for the complete code, setup instructions, and more details:  https://lnkd.in/d8WNwq-9 I am eager to hear your thoughts and feedback! Let’s connect and discuss further possibilities in the field of AI and computer vision! #ObjectDetection #YOLOv5 #DeepLearning #ComputerVision #AI #MachineLearning #DataScience #COCODataset #GitHub #OpenSource