Quick and dirty multiply raw file conversion

Multi-raw2dng-converter

I asume that you know all about installiation and usage of Magic Lanters raw video functionality. 

If you like me find your self with many raw files, using raw2dng manually can be pain in a**.  Here you have python 3.x script working and tested on Windows 8. Given the argument -d "file directory" it will look for any subfolders there and for each raw file in subfolder will create new folder and will run raw2dng on that file. The resulting dng will end up in folder named "ra_file_name" without RAW. The script utilizes as many new processes as there cores in CPU.

Note that this script is just quick and  dirty way to fix my problem. I hope it will be useful for other as well. Feel free to modify and extend.

Usage:

D:\dev\python multiConverter.py -d "F:\Images\2013\0722"

Output:

Successfully processed: F:\Images\2013\0722\1\M17-2243.RAW

Script:

#!/usr/bin/python
#searches for raw files and converts then into a directory with the 
#same name as file
import glob
import sys, getopt
import os, multiprocessing, queue, subprocess
from threading import Thread, Lock

FILE = 0
DIR = 1
RAW2DNG = r"C:path\to\raw2dng.exe"
def optionsGet(argv):
 inputdir = ""
 try:
  opts, args = getopt.getopt(argv,"hd:",["ddir="])
 except getopt.GetoptError:
  print('multiconverter.py -d ')
  sys.exit(2)
 for opt, arg in opts:
  if opt == "-h":
   print("multiconverter.py -d ")
   sys.exit()
  elif opt in ("-d", "--ddirectory"):
   inputdir = arg
 return inputdir

def getCPUs():
 # Windows
    try:
        res = int(os.environ['NUMBER_OF_PROCESSORS'])
        if res > 0:
            return res
    except (KeyError, ValueError):
        pass

def createFolder(name):
 pass
 

def getFileNames(name):
 return glob.glob(name + "\*.RAW")

def getsubdirs(inputdir):
 file_list = []
 dirs=os.listdir(r'%s' %inputdir)
 for d in dirs:
  tmp = r'%s\%s' %(inputdir,d)
  file_list.append(tmp)
 return file_list
  
def createJobs(dir_list, q):
 for d in dir_list:
  files = getFileNames(d)
  for f in files:
   q.put((f,d))
   
  
   
def deployWorkers(file_list, l, num_workers, func):
 jobs = multiprocessing.Queue()
 createJobs(file_list, jobs)
 workers = []
 for i in range(num_workers):
  jobs.put(None)
  tmp = multiprocessing.Process(target=func, args=(jobs,))
  tmp.start()
  workers.append(tmp)
 for worker in workers:
  worker.join()
  
def raw2dngWorker(queue):
 while True:
  job = queue.get()
  if job == None:
   break
  else:
   #enter right dir
   os.chdir(job[DIR])
   #create folder
   folder = job[FILE].split(".")[0]
   os.makedirs(folder)
   #change dir
   os.chdir(folder)
   proc = subprocess.Popen([RAW2DNG, job[FILE]] , 
    stdin=subprocess.PIPE,
    stdout=subprocess.PIPE,
    stderr=subprocess.STDOUT, )
   stdout_value, stderr_value = proc.communicate()
   if not stderr_value:
    print("Successfully processed: %s" %job[FILE])
   else:
    print("ERROR %s " %stderr_value)
   
   
 
   
if __name__ == "__main__":
 inputdir = optionsGet(sys.argv[1:])
 cores = getCPUs()
 l = Lock()
 file_list = getsubdirs(inputdir)

 #start cores = workes
 deployWorkers(file_list, l, cores, raw2dngWorker) 

Cheers