yolo-bdd-inference
Dino-X-API-Demo::Alteredverse
Track points in a video by clicking or using grid
Identify objects in images and videos
Powerful foundation model for zero-shot object tracking
Control object motion in videos using 2D trajectories
YOLOv11n & DeepSeek 1.5B LLM—Running Locally
Detect objects in images or videos
Model Yolo
Product Prototype 1
Track people in a video and capture faces
Video captioning/tracking
Generate a video with stick figures tracking human poses
Yolo Bdd Inference is an AI-powered tool designed to track objects in video and analyze images. It leverages the YOLO (You Only Look Once) algorithm to detect objects in real-time. Yolo Bdd Inference is optimized for high accuracy and speed, making it suitable for applications requiring efficient object detection.
• Real-time object detection: Detect objects in videos and images with minimal latency.
• High accuracy: Utilizes advanced deep learning models for precise object recognition.
• Multi-format support: Compatible with various image and video formats.
• Customizable: Allows users to tweak detection parameters for specific use cases.
• Efficient performance: Optimized for running on both CPUs and GPUs.
git clone https://github.com/your-repository/yolo-bdd-inference.git
pip install -r requirements.txt
python detect.py --input your_input.mp4 --output your_output.mp4
Optional parameters can be added to customize detection settings.What operating systems does Yolo Bdd Inference support?
Yolo Bdd Inference is compatible with Windows, macOS, and Linux.
Can Yolo Bdd Inference detect multiple objects in a single frame?
Yes, Yolo Bdd Inference is capable of detecting multiple objects in a single frame simultaneously.
How can I improve inference speed?
To improve inference speed, consider using a GPU or optimizing the model by reducing the input resolution.