--- tags: - custom-component-track - gradio-custom-component - screen-recorder - PIP - picture-in-picture title: gradio_screenrecorder short_description: Screen Recorder + Picture in Picture Gradio Custom Component colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py license: mit emoji: 🎥 sdk_version: 5.33.1 --- * [Presentation Video](https://www.youtube.com/watch?v=8c9qmeGDp3I) # `gradio_screenrecorder` Static Badge Screen Recorder Gradio Custom Component ## Installation ```bash pip install gradio_screenrecorder ``` ## Usage ```python import gradio as gr from gradio_screenrecorder import ScreenRecorder def handle_recording(recording_data): """Handle recorded video data""" print(f'Received recording data: {recording_data}') if not recording_data or not recording_data.get('video'): return None try: video_info = recording_data['video'] # Return the video path that can be used by the Video component return video_info.get('path') except Exception as e: print(f'Error processing recording: {e}') return None css = """ .screen-recorder-demo { max-width: 800px; margin: 0 auto; } """ with gr.Blocks(css=css, title="Screen Recorder Demo") as demo: gr.HTML("""

Gradio Screen Recorder Component Demo

""") with gr.Row(): with gr.Column(): recorder = ScreenRecorder( audio_enabled=True, webcam_overlay=True, # Disabled for now webcam_position="top-left", recording_format="webm", max_duration=60, label="Screen Recorder" ) with gr.Column(): output_video = gr.Video(label="Recorded Video") # Event handler recorder.change( fn=handle_recording, inputs=recorder, outputs=output_video ) if __name__ == "__main__": demo.launch() ``` ## `ScreenRecorder` ### Initialization
name type default description
audio_enabled ```python bool ``` True None
webcam_overlay ```python bool ``` False None
webcam_position ```python "top-left" | "top-right" | "bottom-left" | "bottom-right" ``` "bottom-right" None
recording_format ```python str ``` "webm" None
max_duration ```python typing.Optional[int][int, None] ``` None None
interactive ```python bool ``` True None
### Events | name | description | |:-----|:------------| | `record_start` | | | `record_stop` | | | `stream_update` | | | `change` | | ### User function The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both). - When used as an Input, the component only impacts the input signature of the user function. - When used as an output, the component only impacts the return signature of the user function. The code snippet below is accurate in cases where the component is used as both an input and an output. ```python def predict( value: typing.Optional[ gradio_screenrecorder.screenrecorder.ScreenRecorderData ][ScreenRecorderData, None] ) -> Unknown: return value ``` ## `ScreenRecorderData` ```python class ScreenRecorderData(GradioModel): video: Optional[FileData] = None duration: Optional[float] = None audio_enabled: bool = True status: Literal["recording", "stopped", "error"] = ( "stopped" ) class Config: json_encoders = { FileData: lambda v: v.model_dump() if v else None } ```