gradio/demo/white_noise_vid_not_playable/run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: white_noise_vid_not_playable"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio opencv-python"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import cv2\n", "import gradio as gr\n", "import numpy as np\n", "\n", "def gif_maker():\n", "    img_array = []\n", "    height, width = 50, 50\n", "    for i in range(30):\n", "        img_array.append(np.random.randint(0, 255, size=(height, width, 3)).astype(np.uint8))\n", "    output_file = \"test.mp4\"\n", "    out = cv2.VideoWriter(output_file, cv2.VideoWriter_fourcc(*'mp4v'), 15, (height, width))  # type: ignore\n", "    for i in range(len(img_array)):\n", "        out.write(img_array[i])\n", "    out.release()\n", "    return output_file, output_file\n", "\n", "demo = gr.Interface(gif_maker, inputs=None, outputs=[gr.Video(), gr.File()])\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}