run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_video_out"]}, {"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": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('video')\n", "!wget -q -O video/compliment_bot_screen_recording_3x.mp4 https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/video/compliment_bot_screen_recording_3x.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import cv2  # type: ignore\n", "import os\n", "from pathlib import Path\n", "import atexit\n", "\n", "current_dir = Path(__file__).resolve().parent\n", "\n", "\n", "def delete_files():\n", "    for p in Path(current_dir).glob(\"*.ts\"):\n", "        p.unlink()\n", "    for p in Path(current_dir).glob(\"*.mp4\"):\n", "        p.unlink()\n", "\n", "\n", "atexit.register(delete_files)\n", "\n", "\n", "def process_video(input_video, stream_as_mp4):\n", "    cap = cv2.VideoCapture(input_video)\n", "\n", "    video_codec = cv2.VideoWriter_fourcc(*\"mp4v\") if stream_as_mp4 else cv2.VideoWriter_fourcc(*\"x264\")  # type: ignore\n", "    fps = int(cap.get(cv2.CAP_PROP_FPS))\n", "    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n", "    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n", "\n", "    iterating, frame = cap.read()\n", "\n", "    n_frames = 0\n", "    n_chunks = 0\n", "    name = str(current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\")\n", "    segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height))  # type: ignore\n", "\n", "    while iterating:\n", "\n", "        # flip frame vertically\n", "        frame = cv2.flip(frame, 0)\n", "        display_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n", "        segment_file.write(display_frame)\n", "        n_frames += 1\n", "        if n_frames == 3 * fps:\n", "            n_chunks += 1\n", "            segment_file.release()\n", "            n_frames = 0\n", "            yield name\n", "            name = str(\n", "                current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\"\n", "            )\n", "            segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height))  # type: ignore\n", "\n", "        iterating, frame = cap.read()\n", "\n", "    segment_file.release()\n", "    yield name\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    gr.Markdown(\"# Video Streaming Out \ud83d\udcf9\")\n", "    with gr.Row():\n", "        with gr.Column():\n", "            input_video = gr.Video(label=\"input\")\n", "            checkbox = gr.Checkbox(label=\"Stream as MP4 file?\", value=False)\n", "        with gr.Column():\n", "            processed_frames = gr.Video(\n", "                label=\"stream\",\n", "                streaming=True,\n", "                autoplay=True,\n", "                elem_id=\"stream_video_output\",\n", "            )\n", "    with gr.Row():\n", "        process_video_btn = gr.Button(\"process video\")\n", "\n", "    process_video_btn.click(process_video, [input_video, checkbox], [processed_frames])\n", "\n", "    gr.Examples(\n", "        [\n", "            [\n", "                os.path.join(\n", "                    os.path.abspath(''),\n", "                    \"video/compliment_bot_screen_recording_3x.mp4\",\n", "                ),\n", "                False,\n", "            ],\n", "            [\n", "                os.path.join(\n", "                    os.path.abspath(''),\n", "                    \"video/compliment_bot_screen_recording_3x.mp4\",\n", "                ),\n", "                True,\n", "            ],\n", "        ],\n", "        [input_video, checkbox],\n", "        fn=process_video,\n", "        outputs=processed_frames,\n", "        cache_examples=False,\n", "    )\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}