![]() In many cases, preferable to a more technically perfect one that, for instance, has a poorer composition or less of what Cartier Bresson called "the decisive moment".Īlso, some flaws can be fixed or improved in editing. Some of the most meaningful images happen to be technically flawed. Technical merit is just part of what a photo is. I don't know of applications that can automatically screen potentially flawed pictures for you, but I wouldn't use them, at least not blindly. I hope this script speeds up your workflow.Ī neat improvement to this script is to include face detection, and compute the blurriness on the biggest faces in the photograph, and use those values for the blurriness threshold, defaulting to the overall bluriness if no faces are detected. Anyway, you should go through the blurred pictures to make sure there's no misplaced keepers in there. However, overall picture measurement means those one-face-and-bokeh-filled-background photographs will be put into the blurry directory, and you'll have to sort them back out. The script works great, and it measures overall picture blurriness. You don't need the newest version of opencv to get this script to run. Or, there are some python+opencv pre-build installs as well. Google python3 for your OS, and how to install pip with it, you can use pip3 to install opencv. Your trickiest issue will be to install python and opencv into your system. Processed %d files into %d blurred, and %d ok.' % (len(files), blur_count, len(files)-blur_count)) If variance_of_laplacian < FOCUS_THRESHOLD: Variance_of_laplacian = cv2.Laplacian(gray, cv2.CV_64F).var() # measure is simply the variance of the Laplacian ![]() # Compute the Laplacian of the image and then the focus Gray = cv2.cvtColor(cv_image, cv2.COLOR_BGR2GRAY) # Sorts pictures in current directory into two subdirs, blurred and okįiles = Here's a quick script that will sort pictures into blurred/ok directories: # Here's a good article on using an open-source computer vision package to detect overall picture blurriness: This is pretty easy to do if you can write in Python. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |