通过时间差算法分组Timelapses

Question

我想编写一个程序，组延时照片的同时从他们的时间戳。该延时照片的和随机的照片的是一个文件夹中。

例如，如果在先前和当前照片之间秒时间戳差值是：346，850，13，14，13，14，15，12，12，13，16，11，438。

你可以做一个合理的猜测的延时开始在13和11结束。

现在，我想一个哈克的解决方案比较与前一个的百分比差异。

但是，必须有一个式/ ALGO到组由为TimeDifference时间戳一起。滚动平均值或东西。

我是不是在寻找一个简单的解决方案？谢谢！

DEF cat_algo（文件夹）：

# Get a list with all the CR2 files in the folder we are processing
file_list = folder_to_file_list(folder)

# Extract the timestamp out of the CR2 file into a sorted dictionary
cr2_timestamp = collections.OrderedDict()
for file in file_list:
    cr2_timestamp[file] = return_date_from_raw(file)
    print str(file) + " - METADATA TIMESTAMP: " + \
        str(return_date_from_raw(file))

# Loop over the dictionary to compare the timestamps and create a new dictionary with a suspected group number per shot
# Make sure we know that there is no first file yet using this (can be refractored)
item_count = 1
group_count = 0
cr2_category = collections.OrderedDict()
# get item and the next item out of the sorted dictionary
for item, nextitem in zip(cr2_timestamp.items(), cr2_timestamp.items()[1::]):

    # if not the first CR2 file
    if item_count >= 2:
        current_date_stamp = item[1]
        next_date_stamp = nextitem[1]

        delta_previous = current_date_stamp - previous_date_stamp
        delta_next = next_date_stamp - current_date_stamp

        try:
            difference_score = int(delta_next.total_seconds() /
                                   delta_previous.total_seconds() * 100)
            print "diffscore: " + str(difference_score)
        except ZeroDivisionError:
            print "zde"

        if delta_previous > datetime.timedelta(minutes=5):
            # if difference_score < 20:
            print item[0] + " - hit - " + str(delta_previous)
            group_count += 1
            cr2_category[item[0]] = group_count
        else:
            cr2_category[item[0]] = group_count

            # create a algo to come up with percentage difference and use this to label timelapses.
        print int(delta_previous.total_seconds())
        print int(delta_next.total_seconds())

        # Calculations done, make the current date stamp the previous datestamp for the next iteration
        previous_date_stamp = current_date_stamp

        # If time difference with previous over X make a dict with name:number, in the end everything which has the
        # same number 5+ times in a row can be assumed as a timelapse.

    else:
        # If it is the first date stamp, assign it the current one to be used in the next loop
        previous_date_stamp = item[1]

    # To help make sure this is not the first image in the sequence.
    item_count += 1

print cr2_category

Answer 1

如果你使用itertools.groupby，使用返回True如果延迟满足你的标准延时照片的区域，根据延迟的名单上的功能，你可以得到每个这样的区域的折射率。基本上，我们分组对功能的真/假输出。

from itertools import groupby

# time differences given in original post
data = [346, 850, 13, 14, 13, 14, 15, 12, 12, 13, 16, 11, 438]

MAX_DELAY = 25 # timelapse regions will have a delay no larger than this
MIN_LENGTH = 3 # timelapse regions will have at least this many photos

index = 0
for timelapse, g in groupby(data, lambda x: x <= MAX_DELAY):
    length = len(list(g))
    if (timelapse and length > MIN_LENGTH):
        print ('timelapse index {}, length {}'.format(index, length))
    index += length

输出：

延时索引2，长度10