| import gradio as gr |
| from Backend.OCR.Dynamic.VideoOCR import gradio_video_ocr_processing |
| def createVideoOcrInterface(): |
| """ |
| Create an interface for OCR in a video. |
| |
| The interface allows users to upload a video, and the model will return an annotated video with bounding boxes and detected text. |
| """ |
| return gr.Interface( |
| fn=gradio_video_ocr_processing, |
| inputs=gr.Video(label="Upload Video File (.mp4)"), |
| outputs=[ |
| gr.Video(label="Annotated Video"), |
| gr.Textbox(label="Gemini Full Response"), |
| gr.JSON(label="Parsed Output") |
| ], |
| title="OCR in Video", |
| description=( |
| "Upload a video for OCR. The model will process the video " |
| "and return an annotated version with bounding boxes and detected text." |
| "It will also process the text with Gemini LLM for manufacturing, expiry date and MRP predictions." |
| ), |
| examples=None, |
| allow_flagging="never", |
| live=False, |
| ) |
|
|
|
|
