Create svision_client.py

svision_client.py

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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.
+    """
+    print("Calling svision to add OCR and face detection...")
+    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