Dynamic Image Processing: Automatically processes a collection of images from a specified directory. Aspect Ratio Maintenance: Resizes images to a target resolution while keeping the original aspect ratio intact. Customizable Output: Users can specify parameters like frame rate, duration, and resolution for the output video. Error Handling: Enhanced error handling to ensure smooth operation and easier debugging. CrossCompute Integration: Designed to work within the CrossCompute framework for automated runs and batch processing.
Python: The backbone scripting language for the project. OpenCV (cv2): Used for image processing and video file creation. CrossCompute: Provides the framework for automating and batching the conversion process.
Creating timelapse videos from a sequence of still images. Generating educational or presentation material from a series of diagrams or photographs. Compiling surveillance or wildlife photography images into video format for easier viewing.