# visualize_uav_trajectory **Repository Path**: Lxk_buaa/visualize_uav_trajectory ## Basic Information - **Project Name**: visualize_uav_trajectory - **Description**: Visualize the trajectory of the drone in the video https://github.com/XXLiu-HNU/visualize_uav_trajectory - **Primary Language**: Unknown - **License**: GPL-3.0 - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2026-01-05 - **Last Updated**: 2026-01-05 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # A tool to visualize the trajectory of drones in videos ## If you have better ideas, welcome to propose them!! Please kindly star ⭐ this project if it helps you Still shot videos: ![gif](./example/speed2-1.gif) And the result: ![result](./example/4tree.png) Although sometimes it can be wrong, this tool works well in certain circumstances. If you are looking for higher quality images, you may need to do it manually! ## Update 1. Added a UI interface for more intuitive display 2. Optimized the generation logic ![result](./example/update.jpg) PS: the video is come from [composite_image](https://github.com/RENyunfan/composite_image) ![result](./example/update2.png) 3. Add more parameters and set gradient transparency overlay ![new_ui](./example/update3.jpg) ## Parameter Description ### 采样间隔(sample_interval_entry) 作用:每隔多少帧进行一次处理(间隔越大,计算越快,但可能导致轨迹不连续)。 默认值:10(每10帧进行一次分析)。 ### 差分阈值(diff_threshold_entry) 作用:用于二值化处理,设置像素差值的阈值(数值越低,检测的运动更灵敏)。 默认值:30(像素差大于30的部分视为运动)。 ### 膨胀核大小(kernel_size_entry) 作用:对检测到的运动区域进行膨胀,以去除噪声(数值越大,运动区域轮廓越平滑)。 默认值:15(15×15的核进行膨胀)。 ### 起始透明度(start_alpha_entry) 作用:决定运动区域最初的透明度(0.0 完全透明,1.0 不透明)。 默认值:0.2(运动区域初始时 20% 透明)。 ### 最终透明度(end_alpha_entry) 作用:控制运动区域的最终透明度(在处理过程中逐渐增加)。 默认值:1.0(最终完全不透明)。 ## Recommend This [project](https://github.com/RENyunfan/composite_image) is also very good ## Disadvantages ### Manual parameter adjustment Please manually select the appropriate parameters according to your own video ### Handling different speeds If the speed of the drone changes in the video, the trajectory may not be good. ### The influence of background If the background moves, such as lighting changes or pedestrian movement, the superposition may be incorrect.