# ChatGPT Translation of Program Code for Image Sketch Abstraction
## 5 Motion Detection with ChatGPT-4
* _Development of Control Systems in Robotics_: skeletal data can be pivotal in developing algorithms for robotic movements or gesture-based control systems, enhancing the interaction between robots and their environment [34]. * _Augmented Reality (AR) Applications_: leveraging the skeleton data can provide a unique interactive experience, overlaying digital information onto real-world objects [35]. ```
Input: The list of frames Output: A new GIF with circles drawn around the prominent object in each frame. For each frame, process to highlight the prominent object: Resize the frame with padding to match the maximum dimensions. Convert the frame to grayscale. Apply Gaussian Blur to reduce noise. Apply thresholding to create a binary image. Find contours in the binary image. Filter out small contours based on a size threshold to remove noise. Identify the largest contour, assuming it is the prominent object. Draw a circle around the largest contour. Save the frame. Save the processed frames with circles as a new GIF. ```

**Algorithm 3**Cheetah in the circle

## 6 Discussion

While summarizing the study results, the researchers would like to present a comparative analysis of semi-automated and fully automated approaches in the context of code conversion from MATLAB to Python to justify the approach taken. This analysis is structured around criteria such as efficiency, accuracy, ease of implementation, flexibility, and user involvement, as shown in Table 4. Fully automated approaches in code conversion or similar computational tasks typically involve advanced algorithms or AI models that can perform tasks with minimal or no human intervention. Examples include deep learning models, where AI models were trained on large datasets to understand and translate code from one programming language to another without human aid, and rule-based conversion tools, where some software used a set of predefined rules to automatically convert code and neural machine translation for code. These AI-driven tools can translate programming languages by learning from vast examples of code conversions [36]. Presented below, Table 4 aids in understanding the trade-offs between the two approaches. As highlighted in the table, fully automated methods offer faster processing and require less human input; at the same time, they may lack precision and adaptability. At the current level of the Large Language Models (LLMs) development, the accuracy they provide and the way they work through the semi-automated approach, with its combination of automated tools and human oversight, chosen by the authors, ensures higher accuracy through manual checks and corrections. It also offers greater flexibility to tailor the process for specific project needs. This balance makes the semi-automated approach more suitable for complex and nuanced tasks such as the conversion from MATLAB to Python, a sophisticated engineering skeletonization code, and the topic of this study. The researchers also want to emphasize the importance of AI pair programming used in this study. While it became a very common and relevant practice in recent years [37], its primary purpose was to leverage the strengths of artificial intelligence (AI) alongside human expertise. In this method, an AI, such as ChatGPT, assists a human programmer, combining the AI's vast data-processing capabilities with the programmer's contextual understanding and problem-solving skills. This synergistic approach enhances the code conversion process's efficiency, accuracy, and innovation. AI can suggest code, identify errors, and offer solutions based on its extensive training, while the human programmer provides the critical thinking and contextual decisions necessary for complex tasks such as MATLAB to Python code conversion. While discussing the role of the ChatGPT bot/model in this study, it is crucial to recognize the unique capabilities of this unique AI tool. ChatGPT was not a helper but a true collaborative partner.