Datasets:
File size: 1,953 Bytes
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import cv2
import os
from pathlib import Path
from rich.progress import (
Progress,
SpinnerColumn,
TextColumn,
BarColumn,
TaskProgressColumn,
MofNCompleteColumn,
)
BASE_DIR = Path("./data")
OUTPUT_DIR = Path("./frames")
affected_dir = BASE_DIR / "affected"
unaffected_dir = BASE_DIR / "unaffected"
dataset = {
"affected": list(affected_dir.glob("*.mp4")),
"unaffected": list(unaffected_dir.glob("*.mp4")),
}
os.makedirs(OUTPUT_DIR, exist_ok=True)
# Define the frame skip, use 1 to extract all frames
FRAME_SKIP = 10
total_frames_to_save = 0
for label, videos in dataset.items():
for video in videos:
cap = cv2.VideoCapture(str(video))
frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
total_frames_to_save += (frames - 1) // FRAME_SKIP + 1
cap.release()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
BarColumn(),
TaskProgressColumn(),
MofNCompleteColumn(),
) as progress:
task = progress.add_task("[cyan]Extracting frames...", total=total_frames_to_save)
for label, videos in dataset.items():
for video in videos:
cap = cv2.VideoCapture(str(video))
video_dir = OUTPUT_DIR / label / video.stem
os.makedirs(video_dir, exist_ok=True)
frameCount = 0
savedFrameCount = 0
while True:
ret, frame = cap.read()
if not ret:
break
if frameCount % FRAME_SKIP == 0:
cv2.imwrite(f"{video_dir}/{frameCount:06d}.jpg", frame)
savedFrameCount += 1
progress.update(task, advance=1)
frameCount += 1
cap.release()
# Print the number of frames extracted
print(
f"Extracted {savedFrameCount} frames from {video} (Total: {frameCount})"
)
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