Skip to main content

50mm f/1.8 AF-D

I'm talking about this lens.
Its made in China, it costs about $130 now, bumped up from about $100 a year back. The focusing ring is dampened and easy to grip (Its a MF on the D40). The mount is metal, but not machined accurately - mine is a tight fit on the camera (and others have commented on this).
The image quality is excellent. This is a set of images of a deck of playing cards shot at the nearest range and at different apertures. The images are 100% crops from center (left) to edge (right). The DOF at f/1.8 is really shallow. The cards look washed out at f/1.8, but if you look at the red diamond and the edge of the middle card, they are sharp, indicating that the DOF is shallow enough (.1" or less) that the card goes out of focus by the time you go from center to edge. At f/2.5 the sharpness and contrast are remarkable:
f/2.5
Labels:

Comments

Post a Comment

Popular posts from this blog

Remove field code from Word document

e.g. before submitting a MS, or hand manipulating some formatting because Word does things (like cross-references) so half-assed [from here ] Select all the text (CTRL-A) Press Ctrl+Shift+F9 Editing to remove anonymous comments that only contain thanks. I really appreciate the thanks, but it makes it harder to find comments that carry pertinent information. I'm also going to try and paste informative comments in the body of the post to make them easier to find.
24 comments
Read more

h5py and multiprocessing

The HDF5 format has been working awesome for me, but I ran into danger when I started to mix it with multiprocessing. It was the worst kind of danger: the intermittent error. Here are the dangers/issues in order of escalation (TL;DR is use a generator to feed data from your file into the child processes as they spawn. It's the easiest way. Read on for harder ways.) An h5py file handle can't be pickled and therefore can't be passed as an argument using pool.map() If you set the handle as a global and access it from the child processes you run the risk of racing which leads to corrupted reads. My personal runin was that my code sometimes ran fine but sometimes would complain that there are NaNs or Infinity in the data. This wasted some time tracking down. Other people have had this kind of problem [ 1 ]. Same problem if you pass the filename and have the different processes open individual instances of the file separately. The hard way to solve this problem is to sw...
Post a Comment
Read more

Reading spreadsheet data in Python: The lack of a good ODS reader

I try and keep long term data in as simple a format as possible, which means text where ever possible. In earlier times I would enter data in excel spreadsheets and then read them from my Python programs using the xlrd package which is excellent. This works well, but in the back of my mind is the thought that someday Microsoft might do something funny with their business model making office software more janky to use and all my fears about keeping data in proprietary formats would come true. Oh, look, that day is today . So, I'm completely abandoning the MS Office suite and going back to basic text files. However, there is a tension between keeping tabulated data in a simple form, such as csv, and entering it in a convenient manner. Excel, of course, nags you everytime you edit a csv file and save it. Libreoffice is excellent: it handles loading and saving in a very streamlined fashion. However, every time you open up the csv file you need to tell Calc what widths you want...
Post a Comment
Read more