VC_perclip.py

import numpy as np
import os
from PIL import Image
#from utils import Evaluator
import sys

def get_common(list_,predlist,clip_num,h,w):
    accs = []
    for i in range(len(list_)-clip_num):
        global_common = np.ones((h,w))
        predglobal_common = np.ones((h,w))

                 
        for j in range(1,clip_num):
            common = (list_[i] == list_[i+j])
            global_common = np.logical_and(global_common,common)
            pred_common = (predlist[i]==predlist[i+j])
            predglobal_common = np.logical_and(predglobal_common,pred_common)
        pred = (predglobal_common*global_common)

        acc = pred.sum()/global_common.sum()
        accs.append(acc)
    return accs
        


DIR='/your/path/to/VSPW_480p'

Pred='./predicts'
split = 'val.txt'

with open(os.path.join(DIR,split),'r') as f:
    lines = f.readlines()
    for line in lines:
        videolist = [line[:-1] for line in lines]
total_acc=[]

clip_num=16


for video in videolist:
    if video[0]=='.':
        continue
    imglist = []
    predlist = []

    images = sorted(os.listdir(os.path.join(DIR,'data',video,'mask')))

    if len(images)<=clip_num:
        continue
    for imgname in images:
        if imgname[0]=='.':
            continue
        img = Image.open(os.path.join(DIR,'data',video,'mask',imgname))
        w,h = img.size
        img = np.array(img)
        imglist.append(img)
        pred = Image.open(os.path.join(Pred,video,imgname))
        pred = np.array(pred)
        predlist.append(pred)
         
    accs = get_common(imglist,predlist,clip_num,h,w)
    print(sum(accs)/len(accs))
    total_acc.extend(accs)
Acc = np.array(total_acc)
Acc = np.nanmean(Acc)
print(Pred)
print('*'*10)
print('VC{} score: {} on {} set'.format(clip_num,Acc,split))
print('*'*10)