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import subprocess
from pathlib import Path
import cv2
import pandas as pd
import os
import numpy as np
def convert_to_mp4(input_path, output_path, data_name):
os.environ['PATH'] += os.pathsep + r"C:\Users\um20242\ffmpeg\bin"
if data_name == 'live_qualcomm':
command = ['ffmpeg.exe', '-hide_banner', '-loglevel', 'error',
'-s', f'1920x1080', '-pix_fmt', 'yuv420p', '-framerate', '25.0',
'-i', str(input_path), '-c:v', 'libx264', '-preset', 'fast', '-c:a', 'aac', '-y',
str(output_path)]
else:
command = ['ffmpeg.exe', '-i', str(input_path), '-c:v', 'libx264', '-preset', 'fast', '-c:a', 'aac', '-y', str(output_path)]
try:
subprocess.run(command, check=True)
print(f"success: {output_path}")
return True
except subprocess.CalledProcessError as e:
print(f"error: {e}")
return False
def is_greyscale_image(image):
if len(image.shape) == 2:
return True
elif len(image.shape) == 3 and image.shape[2] == 3:
b, g, r = image[:, :, 0], image[:, :, 1], image[:, :, 2]
color_threshold = 3
if (cv2.norm(b - g, cv2.NORM_INF) <= color_threshold and
cv2.norm(b - r, cv2.NORM_INF) <= color_threshold and
cv2.norm(g - r, cv2.NORM_INF) <= color_threshold):
return True
return False
def check_video_greyscale(video_path):
cap = cv2.VideoCapture(str(video_path))
if not cap.isOpened():
print(f"Cannot open video file: {video_path}")
return False, False
frame_read = False
while True:
ret, frame = cap.read()
if not ret:
break
frame_read = True
if not is_greyscale_image(frame):
cap.release()
return False, True
cap.release()
# 如果循环结束后没有发现彩色帧，且至少读取到一帧，认为视频是灰度的
return True if frame_read else False, frame_read
def process_videos_from_csv(metadata_path, output_csv, data_name):
df = pd.read_csv(metadata_path)
results = []
for i, row in df.iterrows():
frame_read = True
if data_name == 'youtube_ugc':
video_path = Path("D:/video_dataset/ugc-dataset/youtube_ugc/original_videos") / f"{row['resolution']}P" / f"{row['vid']}.mkv"
elif data_name == 'konvid_1k':
video_path = Path("D:/video_dataset/KoNViD_1k/KoNViD_1k_videos") / f"{row['vid']}.mp4"
elif data_name == 'lsvq_train' or data_name == 'lsvq_test' or data_name == 'lsvq_test_1080P':
video_path = Path("D:/video_dataset/LSVQ") / f"{row['vid']}.mp4"
elif data_name == 'live_vqc':
video_path = Path("D:/video_dataset/LIVE-VQC/video") / f"{row['vid']}.mp4"
elif data_name == 'live_qualcomm':
video_path = Path("D:/video_dataset/LIVE-Qualcomm") / f"{row['vid']}.yuv"
elif data_name == 'cvd_2014':
video_path = Path("D:/video_dataset/CVD2014") / f"{row['vid']}.avi"
converted_path = video_path.with_suffix('.mp4')
need_conversion = data_name == 'live_qualcomm' or not frame_read
if need_conversion:
convert_to_mp4(video_path, converted_path, data_name)
is_greyscale, frame_read = check_video_greyscale(converted_path)
os.remove(converted_path)
else:
is_greyscale, frame_read = check_video_greyscale(video_path) # 直接检查原视频
if is_greyscale:
print(video_path)
results.append({'Index': i, 'vid': row['vid'], 'Is Greyscale': is_greyscale})
if len(results) != 0:
result_df = pd.DataFrame(results)
result_df.to_csv(output_csv, index=False)
print(f"results saved to {output_csv}")
else:
print('no greyscale video')
if __name__ == '__main__':
data_name = 'live_qualcomm'
metadata_path = f'../../metadata/{data_name.upper()}_metadata.csv'
greyscale_path = f'../../metadata/greyscale_report/{data_name.upper()}_greyscale_metadata.csv'
process_videos_from_csv(metadata_path, greyscale_path, data_name)
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