Photographer's Data

Building a portrait of a photographer through metadata.

date

Spring 2017

technologies used

course

This is a collaborative project between myself and Soonho Kwon, a photographer and design major from Carnegie Mellon University. The theme of the assignment was portraits. Due to the experimental nature of the course, and the photography interests we both have, we designed my interpretation of the assignment to be a data visualization, a "portrait of a photographer," using our photograph metadata.

All of the following data portraits were created by first converting our photography to JPGs (Soonho had over 90k RAW images which took over a week to convert). We then ran a custom software I wrote which analyzed each image's metadata for a multitude of datapoints, such as aperture, focal length, ISO rating, etc.

You can view the original project documentation on the class website, and Soonho's interpretation of this portrait assignment here.

Focal Length

This chart shows that I tended to use my 50mm prime and zoom lenses the most. I often used the 50mm for weddings, and did 4 years of sports photography with a telescopic lens. Soonho's favorite lens is in the 35mm range.

The only outlier in this data would be a point-and-shoot that I used to use, which measured in a 9mm but looked more like a standard 18mm photo.

Aperture

Aperture is, among other uses, great for controlling how out of focus the foreground and background are compared to the subject. The smaller the aperture, the thinner the plane of focus is. Click here to learn more about aperture.

I started a majority my photography with beginner's set of lenses, which has a lower quality, higher aperture. Later on I had portrait lenses at 1.8mm and such. However at the time of this data, Soonho had much nicer, lower-aperture lenses in his arsenal.

Ambience (Hızal)

This chart shows that I tended to use my 50mm prime and zoom lenses the most. I often used the 50mm for weddings, and did 4 years of sports photography with a telescopic lens. Soonho's favorite lens is in the 35mm range.

The only outlier in this data would be a point-and-shoot that I used to use, which measured in a 9mm but looked more like a standard 18mm photo.

Ambience (Soonho)

This chart shows that I tended to use my 50mm prime and zoom lenses the most. I often used the 50mm for weddings, and did 4 years of sports photography with a telescopic lens. Soonho's favorite lens is in the 35mm range.

The only outlier in this data would be a point-and-shoot that I used to use, which measured in a 9mm but looked more like a standard 18mm photo.

                        
# Copyright Hizal Celik, 2017
# Cannot use or modify this code without Hizal's permission

from collections import OrderedDict 
from os.path import exists, join
from datetime import datetime
from os import makedirs, walk
import logging, traceback
import exifread
import json

debug = False
default_folder = "imgs"
extentions = ('.jpg','.jpeg','.png','.tif','.tiff','.gif')
files = []
metadata = {}
days = {}
data = []

def load(folder = None):
  global files
  if not folder:
    folder = default_folder

  for r, dir, f in walk(folder):
    for file in f:
      if join(r,file).lower().endswith(extentions):
        files.append(join(r, file))

  perc = 0
  count = 0
  for file in files:
    if debug:
      print file

    image = None
    while not image:
      try:
        image = open(file, 'rb')
      except:
        print "ERROR: File not found: " + file
        raw_input("Press enter to continue when reconnected ");
    
    tags = exifread.process_file(image, details=False)  
    try:
      # timestamp
      ts = datetime.strptime(str(tags['EXIF DateTimeOriginal']), '%Y:%m:%d %H:%M:%S')

      # aperture
      fstop = str(tags['EXIF FNumber']).split('/')
      if len(fstop) > 1:
        f = float(fstop[0])/float(fstop[1])
      else:
        f = float(fstop[0])

      # shutter speed
      speed = str(tags['EXIF ExposureTime']).split('/')
      if len(speed) > 1:
        ss = float(speed[0])/float(speed[1])
      else:
        ss = float(speed[0])
      
      # iso
      iso = int(str(tags['EXIF ISOSpeedRatings']))

      # focal length
      mm = str(tags['EXIF FocalLength']).split('/')
      if len(mm) > 1:
        fl = float(mm[0])/float(mm[1])
      else:
        fl = float(mm[0])

      if debug:
        print "\tTimestamp: " + str(ts)
        print "\tAperture: f" + str(f)
        print "\tShutter: " + str(tags['EXIF ExposureTime']) + " (" + str(ss) + ")"
        print "\tISO: " + str(iso)
        print "\tFocal length: " + str(fl) + "mm"

      metadata[file] = {'f':f, 'ss':ss, 'iso':iso, 'fl':fl, 'ts':ts}

    except Exception as e:
      if debug:
        print file
        logging.error(traceback.format_exc())
      pass

    # print progress
    if count == 0:
      print " 0% ",
    count += 1
    new_perc = int(round(((count * 1.0) / len(files)) * 100))
    if new_perc > perc and new_perc%10==0:
      print "\n" + str(new_perc) + "% ",
    elif new_perc > perc and new_perc%1==0:
      print ".",
    perc = new_perc

  print ""
  print str(len(files)) + " files found.\n"

def write():
  filename = "data.js"
  if debug:
    filename = "debug.txt"

  print "Writing " + filename + "... ",
  with open(filename, 'w') as f:
    f.write("window.chartdata = [\n")
    for day in data:
      f.write("[")
      for i in xrange(len(day)):
        f.write(str(day[i]))
        if i != len(day)-1:
          f.write(',')
        else:
          f.write('],\n')
    f.write("];")
    f.close()

  print "\t\tdone."

def map(value, srcMin, srcMax, tgtMin, tgtMax):
  return tgtMin + (tgtMax - tgtMin) * ((float(value) - srcMin) / (srcMax - srcMin))

def constrain(value, min, max):
  if value < min:
    return min
  if value > max:
    return max
  return value

def getRating(meta):
  iso = constrain(map(meta['iso'], 100, 6400, 0, 100), 0, 100)
  f = constrain(map(meta['f'], 22, 1.4, 0, 100), 0, 100)
  ss = constrain(map(meta['ss'], float(1.0/8000), 1, 0, 100), 0, 100)

  if debug:
    print "\tISO: " + str(meta['iso']) + "/" + str(iso)
    print "\tF: " + str(meta['f']) + "/" + str(f)
    print "\tSS: " + str(meta['ss']) + "/" + str(ss)

  return int(iso + f + ss)

def analyze(index = None):
  global metadata, data, days

  count = 0
  perc = 0
  for img in metadata:
    meta = metadata[img]
    rating = getRating(meta)
    if debug:
      print ""
      print img
      print rating
    if rating >= 250:
      print img

    if str(meta['ts'].date()) in days:
      days[str(meta['ts'].date())].append(rating)
    else:
      days[str(meta['ts'].date())] = [rating]

    # print progress
    count += 1
    new_perc = int(round(((count * 1.0) / len(metadata)) * 100))
    if new_perc > perc and new_perc%10==0:
      print str(new_perc) + "% "
    perc = new_perc

  # save as ordered days
  ordered = OrderedDict(sorted(days.items(), key=lambda t: t[0]))
  for day in ordered:
    data.append(ordered[day])

  if debug:
    print days
    print ordered
    print data

  print str(len(metadata)) + " files processed."

def test():
  pass

while True:
  print "0: Exit (without saving)"
  print "1: Auto"
  print "2: Load"
  print "3: Analyze"
  print "4: Save data"
  choice = (int)(raw_input("> "))

  if choice == 0:
    break

  if choice == 1:
    load()
    analyze()
    write()
    
  elif choice == 2:
    folder = raw_input("Folder section: ")
    load(folder)
  elif choice == 3:
    analyze()
  elif choice == 4:
    write()
  elif choice == 626:
    test()
  else:
    print ""

  print ""
                        
                        
                            ambience.py (source), aperture.py (source), focal.py (source)

Analysis

Python script to analyze ambience. Aperture and focal length analysis was a modified version of this file.

Photographer's Data

category

date

technologies used

course

Focal Length

Aperture

Ambience (Hızal)

Ambience (Soonho)

Analysis