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Implement object detection for bone fractures using YOLOv8 and Python. Learn to load models, process images, and visualize predictions with hands-on coding examples.
Implement YOLOv8 for ship detection in sea views using Python. Learn data preparation, model training, and prediction visualization for effective object detection.
Learn to implement object detection for playing cards using YOLOv8 and Python. Covers model loading, data processing, training, and visualization of predictions and annotations.
Learn to boost YOLOv8's object detection using SAHI library. From installation to implementation, discover how to perform sliced predictions, visualize results, and compare performance with standard YOLOv8 for improved computer vision projects.
Learn to build a custom object detector using Detectron2. Step-by-step guide covers dataset preparation, model training, and making predictions on new images. Ideal for beginners in deep learning and computer vision.
Learn to build an advanced object detection system using DETR, covering data preparation, model implementation, training, and inference with PyTorch, Transformers, and PyTorch Lightning.
Explore AI-driven image processing using Grounding DINO, SAM, and Stable Diffusion. Learn to detect, segment, and generate new images with step-by-step guidance on model integration and custom prompts.
Explore Photomaker to generate AI images featuring your face. Learn installation, Python libraries, and text-prompt techniques for creating personalized, stunning photos effortlessly.
Discover how to transform old, low-quality videos into full HD using AI-powered video enhancement tools, Python libraries, and GPU processing for superior resolution and clarity.
Master the art of animating still images with realistic facial expressions using Live Portrait's free AI technology and Python-based implementation.
Learn to detect floods using Yolo V8 image segmentation. Covers dataset preparation, model training, and testing on new images to generate segmentation masks highlighting flooded areas.
Learn to build and train a custom Detectron2 model for instance segmentation on your own dataset, covering annotation, training on Windows and Linux, and testing on new images.
Generate descriptive captions for images using Python, PyTorch, and Hugging Face's pre-trained 'nlpconnect/vit-gpt2-image-captioning' model. Learn to process images with ViT and generate text with GPT-2.
Generate automatic subtitles for audio and video using Faster-whisper, a faster implementation of OpenAI's Whisper model. Learn to transcribe, create SRT files, and translate subtitles to multiple languages.
Learn to remove objects from images using Inpainter, combining semantic segmentation and EdgeConnect. Master installation, single and multiple object removal for photo editing and data augmentation.
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