I have a set of 5 cameras that operate independently of each other. I need to bin the photo's into a groups of 5 images, taken within say a 1 second window. I have access to the exif tags and can identify the image capture time.
What is the best way to do it ? A psuedo-python code solution is preferred.
Eg.Input:
Cam1 = [002.jpg, 003,jpg, 008.jpg ...]
Cam2 = [005.jpg, 023,jpg, 081.jpg ...]
Cam3 = [014.jpg, 013,jpg, 009.jpg ...]
Cam4 = [011.jpg, 034,jpg, 049.jpg ...]
Cam5 = [001.jpg, 056,jpg, 081.jpg ...]
Expected output:
Grouped = [[002.jpg, 023.jpg, 013.jpg, 049.jpg, 056.jpg], ......]
Here the elements of Grouped[0] all have the same time time stamp.
Get the difference between the capture time and a defined starting time in seconds and put the images in a dictionary with that key.
image_dict = collections.defaultdict(list)
for image in images:
# Will return float
diff = (capture_time - starting_time).total_seconds()
image_dict[int(diff)].append(image)
Then you can convert it to your preferred format:
final = []
for key in sorted(image_dict.keys()):
final.append(image_dict[key])