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Runtime error
Runtime error
File size: 3,347 Bytes
157bd4f 9aa33d8 157bd4f 9aa33d8 157bd4f a2f4d4e 9aa33d8 157bd4f 9aa33d8 157bd4f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 | """Frame extraction and cropping from input videos.
All operations use on-demand cv2.VideoCapture seeking — no frames are
pre-extracted or stored in memory.
"""
import logging
from typing import List, Optional, Tuple
import cv2
import numpy as np
logger = logging.getLogger(__name__)
def extract_frame(video_path: str, frame_idx: int) -> np.ndarray:
"""Extract a single frame from a video by index.
Args:
video_path: Path to the video file.
frame_idx: Zero-based frame index.
Returns:
HxWx3 BGR uint8 numpy array.
Raises:
ValueError: If frame_idx is out of range or video cannot be opened.
FileNotFoundError: If video_path does not exist.
"""
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
raise ValueError(f"Cannot open video file: {video_path}")
try:
total = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
if frame_idx < 0 or frame_idx >= total:
raise ValueError(
f"Frame index {frame_idx} out of range [0, {total})"
)
cap.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
success, frame = cap.read()
if not success or frame is None:
raise ValueError(f"Failed to read frame {frame_idx}")
return frame
finally:
cap.release()
def get_video_info(video_path: str) -> dict:
"""Return video metadata (total_frames, fps, width, height)."""
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
raise ValueError(f"Cannot open video file: {video_path}")
try:
return {
"total_frames": int(cap.get(cv2.CAP_PROP_FRAME_COUNT)),
"fps": cap.get(cv2.CAP_PROP_FPS) or 30.0,
"width": int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
"height": int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)),
}
finally:
cap.release()
def crop_frame(
frame: np.ndarray,
bbox: List[int],
padding: float = 0.15,
) -> np.ndarray:
"""Crop a frame to a bounding box with optional padding.
Args:
frame: HxWx3 BGR numpy array.
bbox: [x1, y1, x2, y2] in pixel coordinates.
padding: Fractional padding around the bbox (0.15 = 15% each side).
Returns:
Cropped HxWx3 BGR numpy array.
"""
x1, y1, x2, y2 = int(bbox[0]), int(bbox[1]), int(bbox[2]), int(bbox[3])
if x2 <= x1 or y2 <= y1:
raise ValueError(
f"Invalid bbox: [{x1}, {y1}, {x2}, {y2}] — must have x2 > x1 and y2 > y1"
)
h, w = frame.shape[:2]
bw = x2 - x1
bh = y2 - y1
pad_x = int(bw * padding)
pad_y = int(bh * padding)
cx1 = max(0, x1 - pad_x)
cy1 = max(0, y1 - pad_y)
cx2 = min(w, x2 + pad_x)
cy2 = min(h, y2 + pad_y)
return frame[cy1:cy2, cx1:cx2].copy()
def frame_to_jpeg(frame: np.ndarray, quality: int = 90) -> bytes:
"""Encode a BGR frame as JPEG bytes.
Args:
frame: HxWx3 BGR numpy array.
quality: JPEG quality (1-100).
Returns:
JPEG bytes.
"""
if frame.dtype != np.uint8:
frame = frame.astype(np.uint8)
encode_param = [int(cv2.IMWRITE_JPEG_QUALITY), quality]
success, buffer = cv2.imencode(".jpg", frame, encode_param)
if not success:
raise RuntimeError("Failed to encode frame as JPEG")
return buffer.tobytes()
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