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import pandas as pd
import subprocess
import json
import os
from scipy.io import loadmat
def parse_framerate(framerate_str):
num, den = framerate_str.split('/')
framerate = float(num)/float(den)
return framerate
def delete_file(file_path):
try:
os.remove(file_path)
except OSError as e:
print(f"error: {e}")
def convert_yuv_to_mp4(yuv_file, output_mp4_file, resolution, pixel_format):
ffmpeg_path = "C://Users//um20242//ffmpeg//bin//ffmpeg.exe"
cmd = f"{ffmpeg_path} -y -s {resolution} -pix_fmt {pixel_format} -i {yuv_file} -c:v libx264 {output_mp4_file}"
try:
subprocess.run(cmd, shell=True, check=True)
except subprocess.CalledProcessError as e:
print(f"error: {e}")
return False
return True
def get_video_metadata(video_file):
print(video_file)
ffprobe_path = "C://Users//um20242//ffmpeg//bin//ffprobe.exe"
cmd = f'{ffprobe_path} -v error -select_streams v:0 -show_entries stream=width,height,nb_frames,r_frame_rate,bit_rate,bits_per_raw_sample,pix_fmt -of json {video_file}'
try:
result = subprocess.run(cmd, shell=True, capture_output=True, check=True)
info = json.loads(result.stdout)
except Exception as e:
print(f"Error processing file {video_file}: {e}")
return {}
# get metadata using ffmpeg
width = info['streams'][0]['width']
height = info['streams'][0]['height']
nb_frames = info['streams'][0].get('nb_frames', 'N/A') # Number of frames might not be available for some formats
pixfmt = info['streams'][0]['pix_fmt']
framerate = info['streams'][0]['r_frame_rate']
framerate = parse_framerate(framerate)
bitdepth = info['streams'][0].get('bits_per_raw_sample', 'N/A')
bitrate = info['streams'][0].get('bit_rate', 'N/A')
print(framerate)
return width, height, nb_frames, pixfmt, framerate, bitdepth, bitrate
def create_dataframe(vid_list, mos_list, width_list, height_list, pixfmt_list, framerate_list, nb_frames_list, bitdepth_list, bitrate_list):
data = {
'vid': vid_list,
'mos': mos_list,
'width': width_list,
'height': height_list,
'pixfmt': pixfmt_list,
'framerate': framerate_list,
'nb_frames': nb_frames_list,
'bitdepth': bitdepth_list,
'bitrate': bitrate_list
}
df_new = pd.DataFrame(data)
return df_new
def extract_csv2metadata(df, video_type):
vid_list = []
mos_list = []
width_list = []
height_list = []
nb_frames_list = []
pixfmt_list = []
framerate_list = []
bitdepth_list = []
bitrate_list = []
if video_type == 'lsvq':
for i in range(len(df)):
video_path = f"D://video_dataset//LSVQ//{df['name'][i]}.mp4"
if os.path.exists(video_path):
vid_list.append(df['name'][i])
mos_list.append(df['mos'][i])
width_list.append(df['width'][i])
height_list.append(df['height'][i])
nb_frames_list.append(df['frame_number'][i])
_, _, _, pixfmt, framerate, bitdepth, bitrate = get_video_metadata(video_path)
pixfmt_list.append(pixfmt)
framerate_list.append(framerate)
bitdepth_list.append(bitdepth)
bitrate_list.append(bitrate)
else:
pass
elif video_type == 'live_vqc':
vid_list = df['vid'].tolist()
vid_list = [vid.replace('.mp4', '') for vid in vid_list]
mos_list = df['mos'].tolist()
width_list = df['width'].tolist()
height_list = df['height'].tolist()
pixfmt_list = df['pixfmt'].tolist()
framerate_list = df['framerate'].tolist()
nb_frames_list = df['nb_frames'].tolist()
bitdepth_list = df['bitdepth'].tolist()
bitrate_list = df['bitrate'].tolist()
df_new = create_dataframe(vid_list, mos_list, width_list, height_list, pixfmt_list, framerate_list, nb_frames_list, bitdepth_list, bitrate_list)
return df_new
def extract_mat2metadata(mat_file, video_type):
data = loadmat(mat_file)
all_variables = {}
for key, value in data.items():
# ignore '__'
if not key.startswith('__') and not key.endswith('__'):
all_variables[key] = value
vid_list = []
mos_list = []
width_list = []
height_list = []
nb_frames_list = []
pixfmt_list = []
framerate_list = []
bitdepth_list = []
bitrate_list = []
for i in range(len(all_variables['video_names'])):
vid = all_variables['video_names'][i].flatten()[0].item()
mos = all_variables['scores'][i].flatten()[0].item()
if video_type == 'cvd_2014':
video_name = vid.replace('.avi', '')
video_path = f"D://video_dataset//CVD2014//{video_name}.avi"
elif video_type == 'live_qualcomm':
video_name = vid.replace('.yuv', '')
tmp_yuv_file = f"D://video_dataset//LIVE-Qualcomm//{video_name}.yuv"
video_path = f"D://video_dataset//LIVE-Qualcomm//{video_name}.mp4"
convert_yuv_to_mp4(tmp_yuv_file, video_path, "1920x1080", "yuv420p")
width, height, nb_frames, pixfmt, framerate, bitdepth, bitrate = get_video_metadata(video_path)
vid_list.append(video_name)
mos_list.append(mos)
width_list.append(width)
height_list.append(height)
nb_frames_list.append(nb_frames)
pixfmt_list.append(pixfmt)
framerate_list.append(framerate)
bitdepth_list.append(bitdepth)
bitrate_list.append(bitrate)
if video_type == 'live_qualcomm':
delete_file(video_path)
df_new = create_dataframe(vid_list, mos_list, width_list, height_list, pixfmt_list, framerate_list, nb_frames_list, bitdepth_list, bitrate_list)
return df_new
def save_to_csv(dataframe, output_path):
dataframe.to_csv(output_path, index=False)
if __name__ == '__main__':
video_type = 'live_vqc'
print(video_type)
# LSVQ
if video_type == 'lsvq':
set_name = 'train' #train, test, test_1080P
df = pd.read_csv(f"D://video_dataset//LSVQ//LSVQ_whole_{set_name}.csv")
df_new = extract_csv2metadata(df, video_type)
print(df_new)
video_type = f'LSVQ_{set_name.upper()}'
# LIVE_VQC
elif video_type == 'live_vqc':
df = pd.read_csv(f"D://video_dataset//LIVE-VQC//LIVE_VQC_metadata.csv")
df_new = extract_csv2metadata(df, video_type)
print(df_new)
# CVD2014
elif video_type == 'cvd_2014':
mat_file = "D://video_dataset//CVD2014//CVD2014info.mat"
df_new = extract_mat2metadata(mat_file, video_type)
print(df_new)
# LIVE-Qualcomm
elif video_type == 'live_qualcomm':
mat_file = "D://video_dataset//LIVE-Qualcomm//LIVE-Qualcomminfo.mat"
df_new = extract_mat2metadata(mat_file, video_type)
print(df_new)
output_csv_path = f'../../metadata/{video_type.upper()}_metadata.csv'
save_to_csv(df_new, output_csv_path)
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