Object Detection (Opencv & Deep Learning)
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Install Python and Opencv (on Windows)
PyCharm IDE (Install, create new projects, useful shortcuts)
Install Opencv with CUDA GPU (on Windows)
Install Darknet with CUDA GPU (on Windows)
4 different Object Detection methods
1.1 OBJECT DETECTION BY COLOR: The HSV Colorspace
1.2 OBJECT DETECTION BY COLOR: Detect objects on an Image and in Real Time
2.1 OBJECT DETECTION ON HOMOGENEOUS BACKGROUND: The Threshold
2.2 OBJECT DETECTION ON HOMOGENEOUS BACKGROUND: Detect objects on an Image and in Real time
3.1 OBJECT DETECTION WITH BACKGROUND SUBTRACTION: Simple background subtraction and MOG
3.2 OBJECT DETECTION WITH BACKGROUND SUBTRACTION: Detect objects on an Image and In Real Time
4.1 OBJECT DETECTION USING FEATURES: What are Features and Feature Matching
4.2 OBJECT DETECTION USING FEATURES: Detect objects on an Image and in Real Time
4.3 OBJECT DETECTION USING FEATURES: Improve the detection with Lowe's ratio test
Object detection with Deep Learning
1. Detect Object with YOLO
2.1 Create an Image Dataset
2.2 Download Dataset from OID (Open Images Dataset)
3.1 Train Custom Object Detector with CUDA GPU (on Windows)
3.2 Train Custom Object Detector with Google Colab
4. Detect Custom Objects
Run YOLO on GPU
Improve the Detection (coming soon)
1. Object Detection vs Object Tracking
2. Object Tracking (with Euclidean Distance)
3. Object Tracking (with SORT)
4. Object Tracking (YOLO + SORT)
5. Object Counting
6. Object Trajectory
Raspberry PI Setup (Install Rasperry PI OS and Opencv)
Detect Objects with Opencv and YOLO
Jetson Nano Setup (Install OS, Opencv and more)
Real time object detection YOLO