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
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.