doc/code/converters/7_video_converters.ipynb (63 lines of code) (raw):

{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Adding Images to a Video\n", "\n", "Adds an image to a video.\n", "To use this converter you'll need to install opencv which can be done with \n", "`pip install pyrit[opencv]`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "ConverterResult(output_text='C:\\\\Users\\\\bjagdagdorj\\\\Documents\\\\tools\\\\pyrit2\\\\PyRIT\\\\dbdata\\\\prompt-memory-entries\\\\videos\\\\1741114936092652.mp4', output_type='video_path')" ] }, "execution_count": null, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pathlib\n", "\n", "from pyrit.common import IN_MEMORY, initialize_pyrit\n", "from pyrit.prompt_converter import AddImageVideoConverter\n", "\n", "initialize_pyrit(memory_db_type=IN_MEMORY)\n", "\n", "input_video = str(pathlib.Path(\".\") / \"..\" / \"..\" / \"..\" / \"assets\" / \"sample_video.mp4\")\n", "input_image = str(pathlib.Path(\".\") / \"..\" / \"..\" / \"..\" / \"assets\" / \"pyrit_architecture.png\")\n", "\n", "video = AddImageVideoConverter(video_path=input_video)\n", "converted_vid = await video.convert_async(prompt=input_image, input_type=\"image_path\") # type: ignore\n", "converted_vid" ] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.9" } }, "nbformat": 4, "nbformat_minor": 2 }