Hello Yaozhi Jiang

#include

#include

using namespace cv;

// Function to define an anchor box based on a given bounding box (adjust as needed)

Rect getAnchorBox(const Rect& bbox) {

// Example: Expand bounding box by 10% in each direction

int offset = 0.1 * (std::max(bbox.width, bbox.height));

return Rect(bbox.x - offset, bbox.y - offset,

bbox.width + 2 * offset, bbox.height + 2 * offset);

}

int main(int argc, char** argv) {

if (argc != 2) {

std::cerr

@Suprava Ranjan Laha，

thank you!

Break down the problem:

• Object Detection: You'll need a library/model for detecting objects in each frame of the video. OpenCV with pre-trained models like YOLO or SSD can be a good starting point.
• Object Tracking: Once objects are detected, you need to track them across frames. Techniques like Kalman Filter or optical flow can be used.
• Bounding Boxes: During tracking, you'll need to generate bounding boxes around the objects.

2. Libraries and Frameworks:

Here are some C++ libraries that can help you with different parts:

• OpenCV: Provides computer vision functionalities like object detection, tracking, and drawing bounding boxes.
• Dlib: Another computer vision library with object detection and tracking capabilities.
• TensorFlow/PyTorch (with C++ API): If you want to use more advanced deep learning models for object detection, these frameworks have C++ APIs.

3. Putting it together:

The C++ code will involve:

• Using OpenCV or another library to read the video frame by frame.
• Applying an object detection model on each frame to identify objects.
• Implementing a tracking algorithm to associate detections across frames.
• Drawing bounding boxes around the tracked objects.

4. Resources:

Here are some resources to get you started:

• OpenCV Tutorials: https://docs.opencv.org/4.x/d9/df8/tutorial_root.html (Look for tutorials on object detection and tracking)
• TensorFlow C++ API: https://www.tensorflow.org/install/lang_c
• PyTorch C++ API: https://pytorch.org/cppdocs/

Additional Notes:

• Auto-anchoring bounding boxes might require additional logic based on your specific needs. It could involve adjusting box size based on object movement or interactions.
• This is a complex task and might require significant coding effort depending on the desired level of accuracy and functionality.

thank you!@Adnan Majeed

5 #ifndef VIDEO_H //if not define 6 #define VIDEO_H 7 8 #include 9 #include 10 11 using namespace std; 12 13 class Video 14 { 15 public: 16 Video(string title , string url, string comment, double length, int rating); 17 ~Video(); 18 void print(); 19 bool longest_length(Video *smallest); 20 bool largest_rating(Video *smallest); 21 bool title_order(Video *smallest); 22 string get_title(); 23 24 25 private: 26 27 double m_length; 28 int m_rating; 29 string m_title; 30 string m_comment; 31 string m_url; 32 33 }; 34 #endif 35

Fakhriddin Boltaboev , thank you!