import os
import glob

videofiles = sorted(glob.glob('scene=*.mp4'))

for video in videofiles:
    cmds="ffmpeg -i "+video+ " -f rawvideo -pixel_format yuv420p /anfs/gfxdisp/hanxue_nerf_data/benchmark_videos_yuv/"+video[:-4]+".yuv"
    print(cmds)
    os.system(cmds)


# # scenelists = ['bears', 'car_fig','extr_farm','extr_woods','glass','intr_farm','intr_woods','metal',]

# # methods = ['directvoxgo','ibrnet_finetune','ibrnet_pretrain','mipnerf','nerf','nex','plenoxel','reference']

# # for scene in scenelists[0:1]:
# #     for method in methods[0:1]:
# #         f = open('vmaf_results.txt', 'a')
# #         cmds = "run_vmaf.py yuv420p 960 768 'scene="+ scene+ ",method=reference.yuv'  'scene="+ scene+ ",method="+method+".yuv' --out-fmt json"
# #         print(cmds)
# #         r = os.popen(cmds)
# #         info = r.readlines()
# #         value=info[-2].strip('\r\n').strip("'VMAF_score':")
# #         print(value)
# #         lines=[]
# #         lines.append(scene)
# #         lines.append(method)
# #         lines.append(value)
# #         lines.append(value)
# #         lines.append(value)        
# #         f.writelines(','.join(lines))
# #         f.write('\n')
# #         f.close()


# scenelists = ['bears', 'car_fig','extr_farm','extr_woods','glass','intr_farm','intr_woods','metal',]

# methods = ['directvoxgo','ibrnet_finetune','ibrnet_pretrain','mipnerf','nerf','nex','plenoxel','reference']

# f_new = open('vmaf_final_results.txt', 'a')
# f = open('vmaf_results.txt', 'r')
# info = f.readlines()
# for line in info:
#     line=line.strip('\r\n')
#     line=line.split(',')[:-1]
#     line.append(line[-1])
#     line.append(line[-1])
#     f_new.writelines(','.join(line))
#     f_new.write('\n')
# f.close()
# f_new.close()
# # value=info[-2].strip('\r\n').strip("'VMAF_score':")
# # print(value)
# # lines=[]
# # lines.append(scene)
# # lines.append(method)
# # lines.append(value)        
# # f.writelines(','.join(lines))
# # f.write('\n')
# # f.close()

# import os
# import glob
# import csv

# scenelists=['bears', 'car_fig', 'extr_farm','extr_woods', 'glass',  'intr_farm', 'intr_woods', 'metal']

# methods=['directvoxgo',  'ibrnet_finetune' , 'ibrnet_pretrain',  'mipnerf',  'nerf',  'nex',  'plenoxel','reference']

# f=open('/home/hl589/benchmark/nerf_vmaf.csv','a')
# writer = csv.writer(f)
# lines = ['condition_id','Q','proc_time']
# writer.writerow(lines)
# f.close()
# f = open('vmaf_final_results.txt', 'r')
# lines=f.readlines()
# results=[line.strip('\n').split(',') for line in lines]
# f.close()
# for method in methods:
#     for scene in scenelists:
#         f=open('/home/hl589/benchmark/nerf_vmaf.csv','a')
#         writer = csv.writer(f)
#         print('currently process',method,scene)
#         lines=[]
#         lines.append(scene+'-'+method)

        
#         for i in range(len(results)):
#             if results[i][0]==scene and results[i][1]==method:
#                 lines.append(results[i][2])
#                 break

#         # lines.append(str(sum(tmp)/len(tmp)))
#         lines.append(0)
#         writer.writerow(lines)
#         f.close()