| import os
|
| import logging
|
| from typing import Iterable
|
|
|
| import cv2
|
| import numpy as np
|
| from tqdm import tqdm
|
|
|
| log = logging.getLogger(__name__)
|
|
|
|
|
| def extract_dji_rgb(
|
| video_path: str,
|
| frame_indices: Iterable[int],
|
| ) -> np.ndarray:
|
| """
|
| Extract selected RGB frames from DJI video (MP4/MKV).
|
|
|
| Parameters:
|
| - video_path: path to the video file recorded by `src/djiRecorder.py`.
|
| - frame_indices: iterable of DJI frame indices to keep
|
| (e.g. the `dji_frame_idx` column from `sync_triples.csv`).
|
|
|
| Returns:
|
| - rgb: array of shape (N, H, W, 3), dtype uint8, RGB frames.
|
|
|
| Note: The video was already flipped (UD+LR) during recording, so no
|
| additional transformations are needed here.
|
| """
|
| if not os.path.exists(video_path):
|
| raise FileNotFoundError(f"DJI video not found: {video_path}")
|
|
|
| indices = np.asarray(list(frame_indices), dtype=np.int64)
|
| if indices.size == 0:
|
| return np.empty((0, 0, 0, 3), dtype=np.uint8)
|
|
|
|
|
| indices = np.unique(indices)
|
| indices_set = set(indices.tolist())
|
|
|
|
|
| cap = cv2.VideoCapture(video_path)
|
| if not cap.isOpened():
|
| raise RuntimeError(f"Failed to open DJI video: {video_path}")
|
|
|
| total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
|
| width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
|
| height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
|
| fps = cap.get(cv2.CAP_PROP_FPS)
|
|
|
| log.info(f"DJI video: {width}x{height} @ {fps:.2f} FPS, {total_frames} frames")
|
| log.info(f"Extracting {len(indices)} frame indices (min={indices.min()}, max={indices.max()})")
|
|
|
| rgb_frames = []
|
| frame_idx = 0
|
| extracted_count = 0
|
|
|
| with tqdm(total=len(indices), desc="DJI extraction", unit="frame") as pbar:
|
| while frame_idx < total_frames:
|
| ret, frame = cap.read()
|
| if not ret:
|
| break
|
|
|
| if frame_idx in indices_set:
|
|
|
| rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
|
| rgb_frames.append(rgb) |
| extracted_count += 1 |
| pbar.update(1) |
| if extracted_count == len(indices): |
| break |
|
|
| frame_idx += 1
|
|
|
| cap.release()
|
| log.info(f"Finished: Extracted {extracted_count}/{len(indices)} DJI frames from {frame_idx} total frames")
|
|
|
| if not rgb_frames:
|
| log.warning("No DJI frames were extracted!")
|
| return np.empty((0, 0, 0, 3), dtype=np.uint8)
|
|
|
| rgb_arr = np.stack(rgb_frames, axis=0)
|
| log.info(f"Final DJI RGB array: {rgb_arr.shape}")
|
|
|
| return rgb_arr
|
|
|
