mirror of
https://github.com/jlengrand/Ivolution.git
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573 lines
22 KiB
Python
573 lines
22 KiB
Python
"""
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.. module:: Facemovie
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:platform: Unix, Windows
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:synopsis: Main class of the application. Contains the core image processing functions, and contains API methods.
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.. moduleauthor:: Julien Lengrand-Lambert <jlengrand@gmail.com>
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"""
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import os
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import sys
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import logging
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import cv
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from util import exif
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import Guy
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from util.Notifier import Observable
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from util.Notifier import Observer
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class FaceMovie(object, Observable, Observer):
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'''
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Main class of the whole application.
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Contains the core image processing functions.
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Takes a bunch of parameters and a list of images and creates the ouput, depending what the user asked for.
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Contains general methods, aimed at being used trough an interface.
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'''
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def __init__(self, face_params):
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"""
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Initializes all parameters of the application. Input and output folders
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are defined, together with the classifier profile.
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:param in_folder: the location where input files will be searched
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:type in_folder: string
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:param out_folder: the location where the outputs will be saved
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:type out_folder: string
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:param face_param: the location of the profile file used to train the classifier
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:type face_param: string
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"""
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Observable.__init__(self) # used to send notifications to process
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Observer.__init__(self, "Library") # used to receive notification to stop
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self.console_logger = logging.getLogger('ConsoleLog') # Used to send messages to the console
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self.my_logger = logging.getLogger('FileLog') # Used to save events into a file
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self.source = face_params.input_folder # Source folder for pictures
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# Retrieving parameters for Face Detection
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self.face_params = face_params
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out_folder = self.face_params.output_folder
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self.out_path = "./data"
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self.out_name = "ivolution"
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self.out_format = "avi"
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# updating the out_folder if needed
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self.check_out_name(out_folder)
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self.sort_method = face_params.sort # sorting by name or using metadata (n or e)
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self.mode = face_params.mode # can be crop or conservative.
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###
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self.guys = [] # List of pictures in source folder
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self.center = [0, 0] # Position of the center in output images (x, y)
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self.dims = [0, 0] # Size of the final output image (x, y). Depends on selected mode
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self.nChannels = 0 # number of channels of the set of images
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self.depth = 0 # depth of the set of images
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self.weight_steps = 5 # number of images to be inserted between each frame to reduce violent switch
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self.speed = [2, 5, 9] # this one should be internal. Number of fps for the video
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self.run = True # command used to stop the processing if needed
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def update(self, message):
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"""
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Used to receive system commands, using the Observer pattern
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"""
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if len(message) == 1: # system command
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self.run = False
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def list_guys(self):
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"""
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Aims at populating the guys list, using the source folder as an input.
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Guys list can be sorted either by name, or using metadata.
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In case source folder is not found; Exits without processing.
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Non Image files are autmatically skipped.
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Source folder is searched recursively. All subfolders are also processed.
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.. note::In case no valid date is found for metadata mode, the images are taken in name order
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"""
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try:
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os.path.exists(self.source)
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os.path.isdir(self.source) # checking if folder exists
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except: # find precise exception
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self.console_logger.critical("Source folder not found ! Exiting. . .")
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self.my_logger.critical("Source folder not found ! Exiting. . .")
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sys.exit(0)
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# loading images, create Guys and store it into guys
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ptr = 0
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for root, _, files in os.walk(self.source):
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for a_file in files:
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ptr += 1
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# notifying the Observers
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self.notify_progress("Processing file", ptr, len(files))
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if self.run: # as long as we want to continue
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guy_source = os.path.join(root, a_file)
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try:
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cv.LoadImage(guy_source) # used to check image is valid
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guy_name = os.path.splitext(a_file)[0]
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# Tries to extract date from metadata
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try:
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guy_date = exif.parse(guy_source)['DateTime']
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except Exception:
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self.my_logger.warning("No metadata found for %s" % (guy_name))
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if self.sort_method == "exif":
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self.console_logger.warning(" No metadata found for %s" % (guy_name))
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guy_date = ''
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a_guy = Guy.Guy(guy_name, guy_date, guy_source)
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# populating guys
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self.guys.append(a_guy)
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except:
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self.console_logger.info("Skipping %s. Not an image file" % (guy_source))
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self.my_logger.info("Skipping %s. Not an image file" % (guy_source))
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self.sort_guys()
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self.console_logger.info("%d guys found in source folder." % (self.number_guys()))
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self.my_logger.info("%d guys found in source folder." % (self.number_guys()))
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def sort_guys(self):
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"""
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Guys list has just been populated, but elements are not ordered yet.
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Sorts the elements of the list either by name or by date extracted from metadata,
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depending on the chosen mode.
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"""
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# Sorting either by exif date or name
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if self.sort_method == "exif":
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self.guys.sort(key=lambda g: g.date)
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else: # default is sort by name
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self.guys.sort(key=lambda g: g.name)
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def search_faces(self):
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"""
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Searches for all faces in the guys we have
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Results to be stored directly in guys
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Takes each image one after the other, and create a guy out of it.
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The Face of each guy is searched.
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In case no face is found, a warning is returned and Guy is set to None
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"""
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ptr = 0
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for a_guy in self.guys:
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ptr += 1
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if self.run:
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a_guy.search_face(self.face_params)
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# notifying the Observers
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self.notify_progress("Processing picture", ptr, self.number_guys())
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if a_guy.has_face(): # face(s) have been found
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self.console_logger.info("Face found for %s" % (a_guy.name))
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self.my_logger.info("Face found for %s" % (a_guy.name))
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else:
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self.console_logger.warning("No face found for %s. Skipped . . ." % (a_guy.name))
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self.my_logger.warning("No face found for %s. Skipped . . ." % (a_guy.name))
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def percent(self, num, den):
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"""
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Returns a float between 0 and 1, being the percentage given by num / den
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"""
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if num > den:
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raise ArithmeticError
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if den <= 0:
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raise ZeroDivisionError
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return (num / float(den))
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def notify_progress(self, message_root, num, den):
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"""
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A notification scheme to quickly notify most common messages
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"""
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# notifying the Observers
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try:
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message = message_root + " %d / %d" % (num, den)
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self.notify([message, self.percent(num, den)])
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except (ArithmeticError, ZeroDivisionError):
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self.notify(["Error", 0])
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def clean_guys(self):
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"""
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Removes all guys for who no face has been found.
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This avoids all has_face loops in the rest of the application
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"""
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return [a_guy for a_guy in self.guys if a_guy.has_face()]
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def prepare_faces(self):
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"""
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Searches for all faces and keep only the one that may be properly used.
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Images without face are discarded.
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The program is exited in case no face is found.
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Searches for the reference size. If will be used later for image resizing, so that
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all faces have the same size.
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"""
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self.search_faces()
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# removes guys that have no faces
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self.guys = self.clean_guys()
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# check that everybody has the same number of channels
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self.check_channels()
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self.check_depth()
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if self.number_guys() == 0:
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self.console_logger.error("No face has been found in the whole repository! Exiting. . . ")
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self.my_logger.error("No face has been found in the whole repository! Exiting. . . ")
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self.notify(["Error", 0])
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sys.exit(0)
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# normalize faces to make them clean
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self.set_guys_ratio() # sets all faces to the same size, by calculating a ratio to a reference
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def check_depth(self):
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"""
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Checks that the depth of all the images in guys is the same
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Sets the depth for the video
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"""
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my_depth = []
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for a_guy in self.guys:
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my_depth.append(a_guy.depth)
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my_depth = list(set(my_depth)) # remove duplicates
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if len(my_depth) != 1:
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# We do not have a unique number of channels for all images
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self.console_logger.error("All images must have the same depth")
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self.my_logger.error("All images must have the same depth")
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else:
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self.depth = my_depth[0]
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def check_channels(self):
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"""
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Checks that the number of channels of all the images in guys is the same
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Sets the number of channels for the video
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"""
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my_chans = []
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for a_guy in self.guys:
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my_chans.append(a_guy.in_channels)
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my_chans = list(set(my_chans)) # remove duplicates
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if len(my_chans) != 1:
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# We do not have a unique number of channels for all images
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self.console_logger.error("All images must have the same number of channels")
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self.my_logger.error("All images must have the same number of channels")
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else:
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self.nChannels = my_chans[0]
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def set_guys_ratio(self):
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"""
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For each Guy, calculates the factor by which the image is going to be resized so that all faces finally have the same size.
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"""
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ref = self.find_reference()
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for a_guy in self.guys:
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a_guy.set_ratio(ref)
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def find_reference(self):
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"""
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Searched for the best face size we want to have.
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Defined (for now), as the smallest of all found faces.
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:returns int - the reference size of the bounding square for faces.
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"""
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references = []
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for a_guy in self.guys:
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if a_guy.has_face():
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references.append(a_guy.faces[0][0][3]) # catch face size (width)
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return min(references)
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def find_final_dimensions(self, cropdims=(0, 0)):
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"""
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Finds the final dimensions that will be needed to create the output.
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Depending on the desired output, it can be
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- (default) the maximal size of the image, by overlapping all images and adding black borders.
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- (crop) the maximal size of the image by overlapping all the images, without adding any black borders
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- (custom crop) A chosen user size, defined as x * y times the head size.
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"""
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if self.mode == "conservative":
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self.find_default_dims()
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elif self.mode == "crop":
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self.find_crop_dims()
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elif self.mode == "custom crop":
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# TODO : implement
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self.console_logger.critical("custom crop is not yet implemented")
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self.my_logger.critical("custom crop is not yet implemented")
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raise Exception
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def find_default_dims(self):
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"""
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Calculates best output image size and position depending on
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faces found in guys.
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The system is simple. The output image should be as big as possible,
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and faces are always placed in the same position. Depending on that,
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the image input image is placed in the output at the correct position.
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Black borders are set everywhere else.
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"""
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# TODO: badly done !
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x_af = 0
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y_af = 0
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ptr = 0
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for a_guy in self.guys:
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if self.run:
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ptr += 1
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# notifying the Observers
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self.notify_progress("Processing picture", ptr, self.number_guys())
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(xc, yc) = a_guy.resized_center()
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(inx, iny) = a_guy.resized_dims()
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# update center
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if xc > self.center[0]:
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self.center[0] = xc
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if yc > self.center[1]:
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self.center[1] = yc
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# update right part
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if (inx - xc) > x_af:
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x_af = inx - xc
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if (iny - yc) > y_af:
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y_af = iny - yc
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self.dims = [x_af + self.center[0], y_af + self.center[1]]
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def find_crop_dims(self):
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"""
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Calculates smallest output image that can be used to avoid adding black borders on image
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It will later be used to create the final image.
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"""
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# TODO: badly done !
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ht = 1000000 # space left above eyes
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hb = 1000000 # space left beneath eyes
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wl = 1000000 # space left left of eyes
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wr = 1000000 # space left right of eyes
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#tr = 0
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ptr = 0
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for a_guy in self.guys:
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if self.run:
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ptr += 1
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# notifying the Observers
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self.notify_progress("Processing picture", ptr, self.number_guys())
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(xc, yc) = a_guy.resized_center()
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(inx, iny) = a_guy.resized_dims()
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# finding width
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if xc < wl:
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wl = xc
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if (inx - xc) < wr:
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wr = inx - xc
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# finding height
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if yc < ht:
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ht = yc
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if (iny - yc) < hb:
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hb = iny - yc
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self.dims = [wl + wr, ht + hb]
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self.center = [wl, ht]
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def get_out_file(self):
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"""
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Reconstructs the final output file for the movie creation
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:returns: String -- The ouput file path to be saved
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"""
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return os.path.join(self.out_path, (self.out_name + "." + self.out_format))
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def save_movie(self):
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"""
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Creates a movie with all faces found in the inputs.
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Guy is skipped if no face is found.
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:param out_folder: the location where to save the output image.
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:type out_folder: string
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:param fps: the number of frames per second to be displayed in final video (3)
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:type fps: int
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"""
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speedrate = self.face_params.speed
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if "win" in sys.platform:
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fourcc = cv.CV_FOURCC('C', 'V', 'I', 'D')
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else: # some kind of Linux/Unix platform
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fourcc = cv.CV_FOURCC('F', 'M', 'P', '4')
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# Corrects frameSize to get a nice video output
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frameSize = self.resizes_for_video_codec() # Fixme : Put in global parameter
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# We have to resize the out_image to make them fit with the desired size
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corr_im = cv.CreateImage(frameSize, self.depth, self.nChannels)
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#frameSize = (652, 498)
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pace = ["slow", "normal", "fast"]
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self.console_logger.info("Speed is set to %s" % (pace[speedrate]))
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self.my_logger.info("Speed is set to %s" % (pace[speedrate]))
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my_video = cv.CreateVideoWriter(self.get_out_file(),
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fourcc,
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self.speed[speedrate],
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frameSize,
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1)
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ii = 0
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for a_guy in self.guys:
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if self.run:
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ii += 1
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self.notify_progress("Saving frame", ii, self.number_guys())
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self.console_logger.info("Saving frame %d / %d" % (ii, self.number_guys()))
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self.my_logger.info("Saving frame %d / %d" % (ii, self.number_guys()))
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out_im = self.prepare_image(a_guy)
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cv.Resize(out_im, corr_im, cv.CV_INTER_LINEAR)
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cv.WriteFrame(my_video, corr_im)
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def show_faces(self, mytime=1000):
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"""
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Show all faces that have been found for the guys.
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The time for which each image will be displayed can be chosen.
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:param mytime: time for which the image should be displayed (in ms) (1000)
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:type mytime: int
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"""
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win_name = " Face Results"
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cv.NamedWindow(win_name, cv.CV_WINDOW_NORMAL)
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cv.ResizeWindow(win_name, 640, 480)
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for a_guy in self.guys:
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if self.run:
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out_im = self.prepare_image(a_guy)
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cv.ShowImage(win_name, out_im)
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cv.WaitKey(mytime)
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cv.DestroyWindow(win_name)
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def save_faces(self, im_format="png"):
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"""
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Save all faces into out_folder, in the given image format
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:param out_folder: the location where to save the output image.
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:type out_folder: string
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:param im_format: Format in which the image should be saved ("png")
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:type im_format: string
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"""
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for a_guy in self.guys:
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if self.run:
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out_im = self.prepare_image(a_guy)
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self.save_guy(out_im, a_guy.name, im_format)
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def number_guys(self):
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"""
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Simply returns the number of guys in the current to-be movie
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.. note::
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Designed for interface use only
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"""
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return len(self.guys)
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def out_display(self, im, name, time=1000, im_x=640, im_y=480):
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"""
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Displays the output image, for time ms.
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Setting time to 0 causes the image to remains open.
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Window name slightly changed to match output
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:param im: the image to be saved, formatted as an OpenCV Image
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:type im: IplImage
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:param name: the name of the image to be saved
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:type name: string
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:param time: time for which the image should be displayed (in ms) (1000)
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:type time: int
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:param im_x: output size of the displayed image (in pixels) (640)
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:type im_x: int
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:param im_y: output size of the displayed image (in pixels) (480)
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:type im_y: int
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"""
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win_name = name + " - out"
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cv.NamedWindow(win_name, cv.CV_WINDOW_NORMAL)
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cv.ResizeWindow(win_name, im_x, im_y)
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cv.ShowImage(win_name, im)
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cv.WaitKey(time)
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cv.DestroyWindow(win_name)
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def check_out_name(self, out_folder):
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"""
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Checks the desired output selected by the user.
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It can be either a folder or a file itself.
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Checks whether the designated path ends with a extension name.
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In case it is, the extension is checked and changed if needed
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|
|
|
:param out_folder: the path slected by the user as output location
|
|
:type out_folder: String
|
|
"""
|
|
|
|
if len(os.path.splitext(out_folder)[1]) > 0: # if ends up with an extension
|
|
self.out_path, complete_name = os.path.split(out_folder)
|
|
self.out_name, format = os.path.splitext(complete_name)
|
|
if format != self.out_format:
|
|
# the format is not compliant with what we can do. We refuse it
|
|
self.my_logger.info("Changing format to avi")
|
|
else:
|
|
# no filename is given. We keep the default
|
|
self.out_path = os.path.split(out_folder)[0]
|
|
|
|
def save_guy(self, im, name, ext):
|
|
"""
|
|
Saves output image to the given format (given in extension)
|
|
|
|
:param im: the image to be saved, formatted as an OpenCV Image
|
|
:type im: IplImage
|
|
:param name: the name of the image to be saved
|
|
:type name: string
|
|
:param out_folder: the location where to save the image
|
|
:type out_folder: string
|
|
:param ext: Format in which the image should be saved ("png")
|
|
:type ext: string
|
|
"""
|
|
file_name = name + "." + ext
|
|
out_name = os.path.join(self.out_path, file_name)
|
|
self.my_logger.info("Saving %s" % (out_name))
|
|
self.console_logger.info("Saving %s" % (out_name))
|
|
|
|
cv.SaveImage(out_name, im)
|
|
|
|
def prepare_image(self, a_guy):
|
|
"""
|
|
Takes a Guy and processes its input image. Prepares the final output image for this
|
|
Guy, so that it is ready to be saved in the desired output.
|
|
|
|
:param a_guy: The Guy currently being processed.
|
|
:type a_guy: Guy
|
|
:returns: IplImage -- The ouput image, created depending on the chosen mode, ready to be saved
|
|
"""
|
|
if self.mode == "conservative":
|
|
out_im = a_guy.create_default_output(self.dims,
|
|
self.center)
|
|
elif self.mode == "crop":
|
|
out_im = a_guy.create_crop_output(self.dims,
|
|
self.center)
|
|
return out_im
|
|
|
|
def resizes_for_video_codec(self):
|
|
"""
|
|
Searches for the closest couple of frameSize so that width*height is a multiple of 4 to avoid weird image encoding.
|
|
|
|
:param frameSize: The desired video output size before correction. (in Pixels)
|
|
:type frameSize: (int, int)
|
|
:returns: corrected frameSize -- The desired output size after correction. In (x, y) form.
|
|
"""
|
|
frameSize = (self.dims[0], self.dims[1])
|
|
|
|
try:
|
|
x, y = frameSize
|
|
except ValueError:
|
|
self.my_logger.error("unknown format for frameSize ")
|
|
return (0, 0)
|
|
|
|
if not(isinstance(x, int)) or not(isinstance(x, int)):
|
|
self.my_logger.error("method expects two integers")
|
|
return (0, 0)
|
|
|
|
while ((x * self.nChannels) % 4) != 0:
|
|
x += 1
|
|
|
|
return (x, y)
|