image_selection_frame.py

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# -*- coding: utf-8 -*-
import Tkinter
import roslib
roslib.load_manifest('face_contour_detector')
import rospy
import cv
import cv_bridge
import Image
import ImageTk
import image_settings_frame
from face_contour_detector.srv import *
from face_contour_detector.msg import *

## @package face_contour_detector.gui.image_selection_frame
#
#  This package contains only the class ImageSelectionFrame. See class documentation for details.
#  @author Fabian Wenzelmann

## @brief constant defining the maximum width an displayed image is allowed to have
MAX_WIDTH = 250
## @brief constant defining the maximum width an displayed image is allowed to have
MAX_HEIGHT = 500

## @brief This class is used to display proposals to the user.
#  @author Fabian Wenzelmann
#
#  This class displays up to four proposals images. The images can be clicked which means that the users selects the filter settings of that image.
#  The images are scaled to a max size so that the four images fit in a single row.
#  Here's an example instance of this frame:
#  @image html image_selection_frame.png
class ImageSelectionFrame(Tkinter.Frame):
        ## @brief Constructor method
        #  @param self the object pointer
        #  @param master The Tkinter master widget of this frame
        #  @param proposals a list of type autoselect_result. Each proposal consists of the original image and the initial filter settings.
        #
        #  This frame contains only for simple labels which display the result of applying the filters of that proposal to the original image.
        #  Each label is clickable. When clicked the settings of this proposal are used to create a ImageSettingsFrame.
    def __init__(self, master, proposals):
        image_settings_frame.current_image = None
        Tkinter.Frame.__init__(self, master)
        self.master.title("Select Edge Image")
        bridge = cv_bridge.CvBridge()
        images = []
        self.proposals = proposals = proposals[:4]
        f = rospy.ServiceProxy("apply_filters", ApplyFilters)
        for proposal in proposals:
            resp = f(proposal.image, proposal.areas)
            cv_img = bridge.imgmsg_to_cv(resp.result_image, "mono8")
            py_img = Image.fromstring("L", cv.GetSize(cv_img), cv_img.tostring())
            scaled = scale_image(py_img, MAX_WIDTH, MAX_HEIGHT)
            images.append(scaled)
        information_label = Tkinter.Label(self, text="Choose one of the following proposals")
        information_label.grid(row=0, column=0)
        button_mode = lambda n: lambda *args: self.select(n)
        # keep references so that there is still the reference (strange tkinter behavior...)
        self.image_buffer = image_buffer = []
        for i, image in enumerate(images):
            photo_image = ImageTk.PhotoImage(image)
            image_buffer.append(photo_image)
            image_label = Tkinter.Label(self, image=photo_image)
            image_label.bind("<1>", button_mode(i))
            image_label.grid(row=1, column=i)
            
        # member documentation
        
        ## @var proposals
        #  a list of type autoselect_result. Each proposal consists of the original image and the initial filter settings.
        
        ## @var image_buffer
        #  a list of the ImateTk.PhotoImages that are displayed (or python will destroy them even if they're displayed...)
    
    ## @brief Callback method for image label clicks.
    #  @param self the object pointer
    #  @param n The number of the proposal that is choose. For example if the list contained for proposals and the second is choosen by the user n is 1
    #
    #  This method creates a new ImageSettingsFrame with the selected initial settings. A new Tkinter.Toplevel widget is created as master of that frame.
    #  The new frame gets displayed and this method waits for this window. After that the master of this object (which is usually a Tkinter.Tk widget) gets destroyed.
    def select(self, n):
        top = Tkinter.Toplevel()
        settings = image_settings_frame.ImageSettingsFrame(top, self.proposals[n])
        settings.pack()
        self.master.withdraw()
        top.wait_window()
        self.master.destroy()
        
## @brief This method is used to scale an image to a maximum size.
#  @param img The image to scale (PIL Image)
#  @param max_width The maximum width that the scaled version of this image is allowed to have
#  @param max_height The maximum height that the scaled version of this image is allowed to have
#
#  This function returns a scaled version of the image. The image has a width <= max_width and a height <= max_height. The scaled version preserve the proportions of the original image.
def scale_image(img, max_width, max_height):
    width, height = img.size
    w_factor, h_factor = max_width / float(width), max_height / float(height)
    factor = min(w_factor, h_factor)
    if factor >= 1:
        return img
    else:
        return img.resize(( int(factor * width), int(factor * height) ), Image.ANTIALIAS)