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import os
os.environ["CUDA_VISIBLE_DEVICES"] = "1"
from gradio_client import Client, handle_file
from typing import Any, Dict, List, Optional, Tuple, Union
import json
# Connect to the remote Space
svision_client = Client("VeuReu/svision")
def extract_scenes(video_path: str, threshold: float = 30.0, offset_frames: int = 5, crop_ratio: float = 0.1):
"""
Call the /scenes_extraction endpoint of the remote Space VeuReu/svision.
Parameters
----------
video_path : str
Path to the input video file.
threshold : float, optional
Scene change detection threshold; higher values make detection less sensitive.
offset_frames : int, optional
Number of frames to include before and after a detected scene boundary.
crop_ratio : float, optional
Ratio for cropping borders before performing scene detection.
Returns
-------
Any
Response returned by the remote /scenes_extraction endpoint.
"""
result = svision_client.predict(
video_file={"video": handle_file(video_path)},
threshold=threshold,
offset_frames=offset_frames,
crop_ratio=crop_ratio,
api_name="/scenes_extraction"
)
return result
def keyframes_every_second_extraction(video_path: str):
"""
Call the /keyframes_every_second_extraction endpoint of the remote Space VeuReu/svision.
Parameters
----------
video_path : str
Path to the input video file.
Returns
-------
Any
Response returned by the remote /keyframes_every_second_extraction endpoint.
"""
result = svision_client.predict(
video_path={"video": handle_file(video_path)},
api_name="/keyframes_every_second_extraction"
)
return result
def add_ocr_and_faces(imagen_path: str, informacion_image: Dict[str, Any], face_col: List[Dict[str, Any]]) -> Dict[str, Any]:
"""
Call the /add_ocr_and_faces endpoint of the remote Space VeuReu/svision.
This function sends an image together with metadata and face collection data
to perform OCR, face detection, and annotation enhancement.
Parameters
----------
imagen_path : str
Path to the input image file.
informacion_image : Dict[str, Any]
Dictionary containing image-related metadata.
face_col : List[Dict[str, Any]]
List of dictionaries representing detected faces or face metadata.
Returns
-------
Dict[str, Any]
Processed output containing OCR results, face detection data, and annotations.
"""
informacion_image_str = json.dumps(informacion_image)
face_col_str = json.dumps(face_col)
result = svision_client.predict(
image=handle_file(imagen_path),
informacion_image=informacion_image_str,
face_col=face_col_str,
api_name="/add_ocr_and_faces"
)
return result
def extract_descripcion_escena(imagen_path: str) -> str:
"""
Call the /describe_images endpoint of the remote Space VeuReu/svision.
This function sends an image to receive a textual description of its visual content.
Parameters
----------
imagen_path : str
Path to the input image file.
Returns
-------
str
Description generated for the given image.
"""
print("Calling svision to describe the scene...")
result = svision_client.predict(
images=[{"image": handle_file(imagen_path)}],
api_name="/describe_images"
)
return result
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