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85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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from dataclasses import dataclass
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from functools import lru_cache
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from typing import Literal
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import cv2
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import numpy as np
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import numpy.typing as npt
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from huggingface_hub import hf_hub_download
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from PIL import Image
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from vllm.multimodal.video import sample_frames_from_video
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from .base import get_cache_dir
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@lru_cache
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def download_video_asset(filename: str) -> str:
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"""
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Download and open an image from huggingface
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repo: raushan-testing-hf/videos-test
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"""
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video_directory = get_cache_dir() / "video-example-data"
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video_directory.mkdir(parents=True, exist_ok=True)
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video_path = video_directory / filename
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video_path_str = str(video_path)
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if not video_path.exists():
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video_path_str = hf_hub_download(
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repo_id="raushan-testing-hf/videos-test",
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filename=filename,
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repo_type="dataset",
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cache_dir=video_directory,
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)
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return video_path_str
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def video_to_ndarrays(path: str, num_frames: int = -1) -> npt.NDArray:
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cap = cv2.VideoCapture(path)
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if not cap.isOpened():
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raise ValueError(f"Could not open video file {path}")
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total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
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frames = []
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for i in range(total_frames):
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ret, frame = cap.read()
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if ret:
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frames.append(frame)
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cap.release()
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frames = np.stack(frames)
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frames = sample_frames_from_video(frames, num_frames)
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if len(frames) < num_frames:
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raise ValueError(f"Could not read enough frames from video file {path}"
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f" (expected {num_frames} frames, got {len(frames)})")
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return frames
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def video_to_pil_images_list(path: str,
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num_frames: int = -1) -> list[Image.Image]:
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frames = video_to_ndarrays(path, num_frames)
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return [
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Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
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for frame in frames
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]
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@dataclass(frozen=True)
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class VideoAsset:
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name: Literal["sample_demo_1.mp4"]
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num_frames: int = -1
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@property
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def pil_images(self) -> list[Image.Image]:
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video_path = download_video_asset(self.name)
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ret = video_to_pil_images_list(video_path, self.num_frames)
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return ret
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@property
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def np_ndarrays(self) -> npt.NDArray:
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video_path = download_video_asset(self.name)
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ret = video_to_ndarrays(video_path, self.num_frames)
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return ret
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