python - 通过时间戳算法将照片分组到游戏中时光倒流

Question

我正在尝试编写一个程序，根据时间戳将延时摄影照片组合在一起。

• 输入文件是我从中读取时间戳的 CR2 RAW 文件
• 时间戳被放入一个排序的字典中，文件名作为键，时间戳作为值

我正在尝试提出一种将照片分类为延时摄影的算法。

假设:

• 延时摄影由至少 5 张以上的连续照片组成

• 延时摄影间隔可能会有所不同，有时间隔 5 分钟，有时间隔 4 秒。

• 一些随机照片是在游戏中时光倒流之间拍摄的

• 只要对大部分时间流逝进行分组，允许轻微的误差是可以的。

一天拍摄的 CR2 原始时间戳可以在这里找到:

Full Dataset: https://pastebin.com/aYmPhYTx

Example:
2018-12-08 11:06:41
2018-12-08 11:09:20
2018-12-08 11:12:29
2018-12-08 11:12:42
2018-12-08 11:12:54
2018-12-08 11:13:07
2018-12-08 11:13:19
2018-12-08 11:13:31
2018-12-08 11:13:44
2018-12-08 11:13:56
2018-12-08 11:14:09
2018-12-08 11:14:21
2018-12-08 11:14:33
2018-12-08 11:14:46
2018-12-08 11:14:58
2018-12-08 11:15:11

以及我目前拥有的代码的摘录。 目前它只检查与前一张照片的时间差是否超过 5 分钟，以查看是否开始了新的延时摄影。这工作正常，但可以改进。

import exifread
import time
import glob
import collections  # for ordered dictionary
import datetime
from itertools import groupby

def cat_algo(folder):
    # 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))

    cr2_category = collections.OrderedDict()
    item_count = 1
    group_count = 0
    sequence_count = 0
    index = 0
    photo_difference_with_previous = collections.OrderedDict()

    # Loop over the dictionary to compare the timestamps and create a new dictionary
    # with a suspected group number per shot.

    # 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:
            # get the datestamp of the current and the next photo in the dict
            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
            previous_difference_score = 0

            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

            # 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

我认为要走的路是使用照片之间的百分比差异，并知道延时摄影是 5 张以上照片的序列，时间方差差异最小。

输出

Day 2/IMG_1995.CR2 - hit - 0:52:14
Day 2/IMG_2040.CR2 - hit - 0:07:01
Day 2/IMG_2117.CR2 - hit - 0:07:15
Day 2/IMG_2186.CR2 - hit - 1:02:05
Day 2/IMG_2206.CR2 - hit - 0:09:38
Day 2/IMG_2220.CR2 - hit - 0:08:45
Day 2/IMG_2372.CR2 - hit - 0:13:01

OrderedDict([('Day 2/IMG_1712.CR2', 0), ('Day 2/IMG_1713.CR2', 0), ('Day 2/IMG_1714.CR2', 0), ('Day 2/IMG_1715.CR2', 0), ('Day 2/IMG_1716.CR2', 0), ('Day 2/IMG_1717.CR2', 0), ('Day 2/IMG_1718.CR2', 0), ('Day 2/IMG_1719.CR2', 0), ('Day 2/IMG_1720.CR2', 0), ('Day 2/IMG_1721.CR2', 0), ('Day 2/IMG_1722.CR2', 0), ('Day 2/IMG_1723.CR2', 0), ('Day 2/IMG_1724.CR2', 0), ('Day 2/IMG_1725.CR2', 0), ('Day 2/IMG_1726.CR2', 0), ('Day 2/IMG_1727.CR2', 0), ('Day 2/IMG_1728.CR2',0), ('Day 2/IMG_1729.CR2', 0), ('Day 2/IMG_1730.CR2', 0), ('Day 2/IMG_1731.CR2', 0), ('Day 2/IMG_1732.CR2', 0), ('Day 2/IMG_1733.CR2', 0), ('Day 2/IMG_1734.CR2', 0), ('Day 2/IMG_1735.CR2', 0), ('Day 2/IMG_1736.CR2', 0), ('Day 2/IMG_1737.CR2', 0), ('Day 2/IMG_1738.CR2', 0), ('Day 2/IMG_1739.CR2', 0), ('Day 2/IMG_1740.CR2', 0), ('Day 2/IMG_1741.CR2', 0), ('Day 2/IMG_1742.CR2', 0), ('Day 2/IMG_1743.CR2', 0), ('Day 2/IMG_1744.CR2', 0), ('Day 2/IMG_1745.CR2', 0), ('Day 2/IMG_1746.CR2', 0), ('Day 2/IMG_1747.CR2', 0), ('Day 2/IMG_1748.CR2', 0), ('Day 2/IMG_1749.CR2', 0), ('Day 2/IMG_1750.CR2', 0), ('Day 2/IMG_1751.CR2', 0), ('Day 2/IMG_1752.CR2'.......

但是经过实验我还没有弄明白。有没有聪明的方法来做到这一点？我在寻找一个简单的解决方案吗？谢谢!

Answer 1

还有另一种实现方式:

import datetime

def diff(time1, time2):
    t1 = datetime.datetime.strptime(time1, '%Y-%m-%d %H:%M:%S')
    t2 = datetime.datetime.strptime(time2, '%Y-%m-%d %H:%M:%S')
    return t2-t1

with open('file.txt', 'r') as f:
        data = f.read()
        dates = [x for x in data.split('\n')]

r = []
result = []
for i in range(len(dates)-1):
    if diff(dates[i], dates[i+1]).total_seconds() > 300:
        result.append(r)
        r = []
    r.append(dates[i])
result.append(r)

for i, r in enumerate(result):
    print('Timelapse: {}. Photos: {}. Period: {} - {}. Duration: {}'.format(i+1, len(r), r[0], r[-1], diff(r[0], r[-1])))

按延时分割的日期:

[['2018-12-08 11:06:41', '2018-12-08 11:09:20', '2018-12-08 11:12:29', '2018-12-08 11:12:42', '2018-12-08 11:12:54', '2018-12-08 11:13:07', '2018-12-08 11:13:19', '2018-12-08 11:13:31', '2018-12-08 11:13:44', '2018-12-08 11:13:56', '2018-12-08 11:14:09', '2018-12-08 11:14:21', '2018-12-08 11:14:33', '2018-12-08 11:14:46', '2018-12-08 11:14:58', '2018-12-08 11:15:11', '2018-12-08 11:15:23', '2018-12-08 11:15:35', '2018-12-08 11:15:48', '2018-12-08 11:16:00', '2018-12-08 11:16:13', '2018-12-08 11:16:25', '2018-12-08 11:16:37', '2018-12-08 11:16:50', '2018-12-08 11:17:02', '2018-12-08 11:17:15', '2018-12-08 11:17:27', '2018-12-08 11:17:40', '2018-12-08 11:17:52', '2018-12-08 11:18:04', '2018-12-08 11:18:17', '2018-12-08 11:18:29', '2018-12-08 11:18:42', '2018-12-08 11:18:54', '2018-12-08 11:19:06', '2018-12-08 11:19:19', '2018-12-08 11:19:31', '2018-12-08 11:19:44', '2018-12-08 11:19:56', '2018-12-08 11:20:08', '2018-12-08 11:20:21', '2018-12-08 11:20:33', '2018-12-08 11:20:46', '2018-12-08 11:20:58', '2018-12-08 11:21:10', '2018-12-08 11:21:23', '2018-12-08 11:21:35', '2018-12-08 11:21:48', '2018-12-08 11:22:00', '2018-12-08 11:22:13', '2018-12-08 11:22:25', '2018-12-08 11:22:37', '2018-12-08 11:22:50', '2018-12-08 11:23:02', '2018-12-08 11:23:15', '2018-12-08 11:23:27', '2018-12-08 11:23:39', '2018-12-08 11:23:52', '2018-12-08 11:24:04', '2018-12-08 11:24:17', '2018-12-08 11:24:29', '2018-12-08 11:24:41', '2018-12-08 11:24:54', '2018-12-08 11:25:06', '2018-12-08 11:25:19', '2018-12-08 11:25:31', '2018-12-08 11:25:44', '2018-12-08 11:25:56', '2018-12-08 11:26:08', '2018-12-08 11:26:21', '2018-12-08 11:26:33', '2018-12-08 11:26:46', '2018-12-08 11:26:58', '2018-12-08 11:27:10', '2018-12-08 11:27:23', '2018-12-08 11:27:35', '2018-12-08 11:27:48', '2018-12-08 11:28:00', '2018-12-08 11:28:12', '2018-12-08 11:28:25', '2018-12-08 11:28:37', '2018-12-08 11:28:50', '2018-12-08 11:29:02', '2018-12-08 11:29:14', '2018-12-08 11:29:27', '2018-12-08 11:29:39', '2018-12-08 11:29:52', '2018-12-08 11:30:04', '2018-12-08 11:30:17', '2018-12-08 11:30:29', '2018-12-08 11:30:41', '2018-12-08 11:30:54', '2018-12-08 11:31:06', '2018-12-08 11:31:19', '2018-12-08 11:31:31', '2018-12-08 11:31:43', '2018-12-08 11:31:56', '2018-12-08 11:32:08', '2018-12-08 11:32:21', '2018-12-08 11:32:33', '2018-12-08 11:32:45', '2018-12-08 11:32:58', '2018-12-08 11:33:10', '2018-12-08 11:33:23', '2018-12-08 11:33:35', '2018-12-08 11:33:47', '2018-12-08 11:34:00', '2018-12-08 11:34:12', '2018-12-08 11:34:25', '2018-12-08 11:34:37', '2018-12-08 11:34:50', '2018-12-08 11:35:02', '2018-12-08 11:35:14', '2018-12-08 11:35:27', '2018-12-08 11:35:39', '2018-12-08 11:35:52', '2018-12-08 11:36:04', '2018-12-08 11:36:16', '2018-12-08 11:36:29', '2018-12-08 11:36:41', '2018-12-08 11:36:54', '2018-12-08 11:37:06', '2018-12-08 11:37:18', '2018-12-08 11:37:31', '2018-12-08 11:37:43', '2018-12-08 11:37:56', '2018-12-08 11:38:08', '2018-12-08 11:38:20', '2018-12-08 11:38:58', '2018-12-08 11:39:01', '2018-12-08 11:39:04', '2018-12-08 11:39:10', '2018-12-08 11:39:23', '2018-12-08 11:39:35', '2018-12-08 11:39:47', '2018-12-08 11:40:00', '2018-12-08 11:40:12', '2018-12-08 11:40:25', '2018-12-08 11:40:37', '2018-12-08 11:40:49', '2018-12-08 11:41:02', '2018-12-08 11:41:14', '2018-12-08 11:41:27', '2018-12-08 11:41:39', '2018-12-08 11:41:51', '2018-12-08 11:42:04', '2018-12-08 11:42:16', '2018-12-08 11:42:29', '2018-12-08 11:42:41', '2018-12-08 11:42:53', '2018-12-08 11:43:06', '2018-12-08 11:43:18', '2018-12-08 11:43:31', '2018-12-08 11:43:43', '2018-12-08 11:43:56', '2018-12-08 11:44:08', '2018-12-08 11:44:20', '2018-12-08 11:44:33', '2018-12-08 11:44:45', '2018-12-08 11:44:58', '2018-12-08 11:45:10', '2018-12-08 11:45:22', '2018-12-08 11:45:35', '2018-12-08 11:45:47', '2018-12-08 11:46:00', '2018-12-08 11:46:12', '2018-12-08 11:46:24', '2018-12-08 11:46:37', '2018-12-08 11:46:49', '2018-12-08 11:47:02', '2018-12-08 11:47:14', '2018-12-08 11:47:26', '2018-12-08 11:47:39', '2018-12-08 11:47:51', '2018-12-08 11:48:04', '2018-12-08 11:48:16', '2018-12-08 11:48:29', '2018-12-08 11:48:41', '2018-12-08 11:48:53', '2018-12-08 11:49:06', '2018-12-08 11:49:18', '2018-12-08 11:49:31', '2018-12-08 11:49:43', '2018-12-08 11:49:55', '2018-12-08 11:50:08', '2018-12-08 11:50:20', '2018-12-08 11:50:33', '2018-12-08 11:50:45', '2018-12-08 11:50:57', '2018-12-08 11:51:10', '2018-12-08 11:51:22', '2018-12-08 11:51:35', '2018-12-08 11:51:47', '2018-12-08 11:51:59', '2018-12-08 11:52:12', '2018-12-08 11:52:24', '2018-12-08 11:52:37', '2018-12-08 11:52:49', '2018-12-08 11:53:02', '2018-12-08 11:53:14', '2018-12-08 11:53:26', '2018-12-08 11:53:39', '2018-12-08 11:53:51', '2018-12-08 11:54:04', '2018-12-08 11:54:16', '2018-12-08 11:54:28', '2018-12-08 11:54:41', '2018-12-08 11:54:53', '2018-12-08 11:55:06', '2018-12-08 11:55:18', '2018-12-08 11:55:30', '2018-12-08 11:55:43', '2018-12-08 11:55:55', '2018-12-08 11:56:08', '2018-12-08 11:56:20', '2018-12-08 11:56:33', '2018-12-08 11:56:45', '2018-12-08 11:56:57', '2018-12-08 11:57:10', '2018-12-08 11:57:22', '2018-12-08 11:57:35', '2018-12-08 11:57:47', '2018-12-08 11:57:59', '2018-12-08 11:58:12', '2018-12-08 11:58:24', '2018-12-08 11:58:37', '2018-12-08 11:58:49', '2018-12-08 11:59:01', '2018-12-08 11:59:14', '2018-12-08 11:59:26', '2018-12-08 11:59:39', '2018-12-08 11:59:51', '2018-12-08 12:00:03', '2018-12-08 12:00:16', '2018-12-08 12:00:28', '2018-12-08 12:00:41', '2018-12-08 12:00:53', '2018-12-08 12:01:06', '2018-12-08 12:01:18', '2018-12-08 12:01:30', '2018-12-08 12:01:43', '2018-12-08 12:01:55', '2018-12-08 12:02:08', '2018-12-08 12:02:20', '2018-12-08 12:02:32', '2018-12-08 12:02:45', '2018-12-08 12:02:57', '2018-12-08 12:03:10', '2018-12-08 12:03:22', '2018-12-08 12:03:34', '2018-12-08 12:03:47', '2018-12-08 12:03:59', '2018-12-08 12:04:12', '2018-12-08 12:04:24', '2018-12-08 12:04:36', '2018-12-08 12:04:49', '2018-12-08 12:05:01', '2018-12-08 12:05:14', '2018-12-08 12:05:26', '2018-12-08 12:05:39', '2018-12-08 12:05:51', '2018-12-08 12:06:03', '2018-12-08 12:06:16', '2018-12-08 12:06:28', '2018-12-08 12:06:41', '2018-12-08 12:06:53', '2018-12-08 12:07:05', '2018-12-08 12:07:18', '2018-12-08 12:07:30', '2018-12-08 12:07:43', '2018-12-08 12:07:55', '2018-12-08 12:08:07', '2018-12-08 12:08:20', '2018-12-08 12:08:32', '2018-12-08 12:08:45', '2018-12-08 12:08:57', '2018-12-08 12:09:09', '2018-12-08 12:09:22', '2018-12-08 12:09:34', '2018-12-08 12:09:47', '2018-12-08 12:09:59'], ['2018-12-08 12:10:12', '2018-12-08 13:02:26', '2018-12-08 13:02:49', '2018-12-08 13:03:08', '2018-12-08 13:03:29', '2018-12-08 13:03:56', '2018-12-08 13:04:22', '2018-12-08 13:04:45', '2018-12-08 13:04:59', '2018-12-08 13:05:25', '2018-12-08 13:05:42', '2018-12-08 13:05:56', '2018-12-08 13:06:16', '2018-12-08 13:06:38', '2018-12-08 13:06:54', '2018-12-08 13:07:13', '2018-12-08 13:07:31', '2018-12-08 13:07:48', '2018-12-08 13:08:12', '2018-12-08 13:08:35', '2018-12-08 13:08:54', '2018-12-08 13:09:27', '2018-12-08 13:09:52', '2018-12-08 13:10:14', '2018-12-08 13:10:31', '2018-12-08 13:10:47', '2018-12-08 13:11:05', '2018-12-08 13:11:38', '2018-12-08 13:12:00', '2018-12-08 13:12:20', '2018-12-08 13:12:35', '2018-12-08 13:13:07', '2018-12-08 13:13:29', '2018-12-08 13:14:07', '2018-12-08 13:14:37', '2018-12-08 13:15:06', '2018-12-08 13:15:32', '2018-12-08 13:15:53', '2018-12-08 13:16:05', '2018-12-08 13:16:26', '2018-12-08 13:17:26', '2018-12-08 13:17:45', '2018-12-08 13:18:06'], ['2018-12-08 13:19:03', '2018-12-08 13:26:04', '2018-12-08 13:26:12', '2018-12-08 13:27:48', '2018-12-08 13:28:11', '2018-12-08 13:28:15', '2018-12-08 13:28:33', '2018-12-08 13:28:57', '2018-12-08 13:29:42', '2018-12-08 13:30:12', '2018-12-08 13:30:37', '2018-12-08 13:30:51', '2018-12-08 13:31:27', '2018-12-08 13:31:43', '2018-12-08 13:32:05', '2018-12-08 13:32:26', '2018-12-08 13:32:44', '2018-12-08 13:33:11', '2018-12-08 13:33:36', '2018-12-08 13:33:56', '2018-12-08 13:34:13', '2018-12-08 13:34:32', '2018-12-08 13:34:52', '2018-12-08 13:35:11', '2018-12-08 13:35:34', '2018-12-08 13:35:51', '2018-12-08 13:36:17', '2018-12-08 13:36:40', '2018-12-08 13:37:00', '2018-12-08 13:37:14', '2018-12-08 13:37:29', '2018-12-08 13:37:45', '2018-12-08 13:38:06', '2018-12-08 13:38:28', '2018-12-08 13:38:52', '2018-12-08 13:39:15', '2018-12-08 13:39:39', '2018-12-08 13:40:04', '2018-12-08 13:40:26', '2018-12-08 13:40:42', '2018-12-08 13:40:59', '2018-12-08 13:41:17', '2018-12-08 13:41:39', '2018-12-08 13:42:13', '2018-12-08 13:42:30', '2018-12-08 13:42:45', '2018-12-08 13:43:01', '2018-12-08 13:43:21', '2018-12-08 13:43:45', '2018-12-08 13:44:10', '2018-12-08 13:44:35', '2018-12-08 13:44:53', '2018-12-08 13:45:22', '2018-12-08 13:45:41', '2018-12-08 13:45:55', '2018-12-08 13:46:06', '2018-12-08 13:46:19', '2018-12-08 13:46:43', '2018-12-08 13:47:02', '2018-12-08 13:47:19', '2018-12-08 13:47:38', '2018-12-08 13:47:55', '2018-12-08 13:48:10', '2018-12-08 13:48:29', '2018-12-08 13:48:53', '2018-12-08 13:49:08', 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统计分类:

Timelapse: 1. Photos: 281. Period: 2018-12-08 11:06:41 - 2018-12-08 12:09:59. Duration: 1:03:18
Timelapse: 2. Photos: 43. Period: 2018-12-08 12:10:12 - 2018-12-08 13:18:06. Duration: 1:07:54
Timelapse: 3. Photos: 76. Period: 2018-12-08 13:19:03 - 2018-12-08 13:52:34. Duration: 0:33:31
Timelapse: 4. Photos: 69. Period: 2018-12-08 13:52:50 - 2018-12-08 14:27:33. Duration: 0:34:43
Timelapse: 5. Photos: 20. Period: 2018-12-08 14:27:51 - 2018-12-08 15:35:39. Duration: 1:07:48
Timelapse: 6. Photos: 14. Period: 2018-12-08 15:35:40 - 2018-12-08 15:46:01. Duration: 0:10:21
Timelapse: 7. Photos: 152. Period: 2018-12-08 15:46:02 - 2018-12-08 16:09:03. Duration: 0:23:01
Timelapse: 8. Photos: 143. Period: 2018-12-08 16:09:11 - 2018-12-08 17:29:18. Duration: 1:20:07