Image Segmentation | Telegram Bot | Deep Learning
🩸 Blood Cell Segmentation Telegram Bot using Deep Learning (FCN-ResNet50) 🔬
👉 Send a blood cell image on Telegram and get pixel-wise segmentation results in seconds!
In this video, I walk you through an AI-powered Telegram bot that performs semantic segmentation on microscopic blood cell images using a custom-trained FCN-ResNet50 model in PyTorch.
The bot automatically:
✅ Accepts a blood cell image
✅ Segments red blood cells (RBCs) from the background
✅ Sends back a color-coded segmented image
This tool is perfect for:
🧫 Medical image analysis
📊 Biomedical research
⚡ Real-time deployment and inference
👨⚕️ Assisting in diagnostics and lab work
🔧 Tech Stack:
PyTorch 🧠
Torchvision 🖼️
OpenCV 📷
PIL 🖌️
python-telegram-bot 🤖
📥 Source Code (GitHub):
🔗 https://github.com/NitinCVOrbit/Blood...
👍 Like | 💬 Comment | 🔔 Subscribe for more AI & Deep Learning projects
📧 For collaboration, contact me: [email protected]
📌 Hashtags:
#DeepLearning #SemanticSegmentation #TelegramBot #PyTorch #MedicalAI #FCN #ResNet50 #BloodCellSegmentation #ComputerVision #Microscopy #HealthcareAI #BiomedicalAI #ImageSegmentation #PythonProject #AIProject #OpenCV #TelegramAI