mirror of
https://github.com/Deepshift/DeepCreamPy.git
synced 2024-11-28 02:09:43 +00:00
integrate in one UI
This commit is contained in:
ccppoo
parent
7303c3d8ec
commit
f5a1b34066
103
decensor.py
103
decensor.py
@ -29,8 +29,8 @@ except ImportError as e:
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print("install Anaconda : https://www.anaconda.com/distribution/ \n")
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class Decensor(QtCore.QThread):
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def __init__(self, text_edit = None, text_cursor = None, ui_mode = None):
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super().__init__()
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def __init__(self, parentThread = None, text_edit = None, text_cursor = None, ui_mode = None):
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super().__init__(parentThread)
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args = config.get_args()
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self.is_mosaic = args.is_mosaic
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self.variations = args.variations
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@ -41,20 +41,29 @@ class Decensor(QtCore.QThread):
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self.signals = None # Signals class will be given by progressWindow
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if ui_mode is not None:
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self.ui_mode = ui_mode
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else:
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self.ui_mode = args.ui_mode
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self.model = None
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self.warm_up = False
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# if ui_mode is not None:
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# self.ui_mode = ui_mode
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# else:
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# self.ui_mode = args.ui_mode
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#
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# if self.ui_mode:
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# self.text_edit = text_edit
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# self.text_cursor = text_cursor
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# self.ui_mode = True
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if not os.path.exists(self.decensor_output_path):
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os.makedirs(self.decensor_output_path)
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if self.ui_mode:
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self.text_edit = text_edit
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self.text_cursor = text_cursor
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self.ui_mode = True
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def run(self):
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if not self.warm_up :
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print("if self.warm_up :")
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self.load_model()
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return
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elif self.warm_up:
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print("elif not self.warm_up:")
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self.decensor_all_images_in_folder()
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def stop(self):
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@ -69,15 +78,23 @@ class Decensor(QtCore.QThread):
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return mask
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def load_model(self):
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self.signals.update_progress_LABEL.emit("load_model()", "Loading neural network. This may take a while.")
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self.signals.insertText_progressCursor.emit("Loading model ... please wait ...\n")
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if self.model is None :
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self.model = InpaintNN(bar_model_name = "./models/bar/Train_775000.meta",
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bar_checkpoint_name = "./models/bar/",
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mosaic_model_name = "./models/mosaic/Train_290000.meta",
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mosaic_checkpoint_name = "./models/mosaic/",
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is_mosaic=self.is_mosaic)
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self.warm_up = True
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print("load model finished")
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self.signals.insertText_progressCursor.emit("Loading model finished!\n")
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self.signals.update_decensorButton_Text.emit("Decensor Your Images")
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self.signals.update_decensorButton_Enabled.emit(True)
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def decensor_all_images_in_folder(self):
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#load model once at beginning and reuse same model
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if not self.warm_up :
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# incase of running by source code
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self.load_model()
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input_color_dir = self.decensor_input_path
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@ -87,24 +104,37 @@ class Decensor(QtCore.QThread):
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output_dir = self.decensor_output_path
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# Change False to True before release --> file.check_file(input_dir, output_dir, True)
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self.signals.update_progress_LABEL.emit("file.check_file()", "Checking image files and directory...")
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# self.signals.update_progress_LABEL.emit("file.check_file()", "Checking image files and directory...")
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self.signals.insertText_progressCursor.emit("Checking image files and directory...\n")
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file_names, self.files_removed = file.check_file(input_dir, output_dir, False)
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self.signals.total_ProgressBar_update_MAX_VALUE.emit("set total progress bar MaxValue : "+str(len(file_names)),len(file_names))
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# self.signals.total_ProgressBar_update_MAX_VALUE.emit("set total progress bar MaxValue : "+str(len(file_names)),len(file_names))
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'''
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print("set total progress bar MaxValue : "+str(len(file_names)))
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self.signals.update_ProgressBar_MAX_VALUE.emit(len(file_names))
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'''
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self.signals.insertText_progressCursor.emit("Decensoring {} image files\n".format(len(file_names)))
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#convert all images into np arrays and put them in a list
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for n, file_name in enumerate(file_names, start = 1):
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self.signals.total_ProgressBar_update_VALUE.emit("Decensoring {} / {}".format(n, len(file_names)), n)
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# self.signals.total_ProgressBar_update_VALUE.emit("Decensoring {} / {}".format(n, len(file_names)), n)
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'''
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self.update_ProgressBar_SET_VALUE.emit(n)
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print("Decensoring {} / {}".format(n, len(file_names)))
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'''
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self.signals.insertText_progressCursor.emit("Decensoring image file : {}\n".format(file_name))
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# signal progress bar value == masks decensored on image ,
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# e.g) sample image : 17
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self.signals.signal_ProgressBar_update_VALUE.emit("reset value", 0) # set to 0 for every image at start
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self.signals.update_progress_LABEL.emit("for-loop, \"for file_name in file_names:\"","Decensoring : "+str(file_name))
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# self.signals.signal_ProgressBar_update_VALUE.emit("reset value", 0) # set to 0 for every image at start
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# self.signals.update_progress_LABEL.emit("for-loop, \"for file_name in file_names:\"","Decensoring : "+str(file_name))
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color_file_path = os.path.join(input_color_dir, file_name)
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color_basename, color_ext = os.path.splitext(file_name)
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if os.path.isfile(color_file_path) and color_ext.casefold() == ".png":
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print("--------------------------------------------------------------------------")
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print("Decensoring the image {}".format(color_file_path))
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print("Decensoring the image {}\n".format(color_file_path))
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try :
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colored_img = Image.open(color_file_path)
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except:
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@ -131,20 +161,25 @@ class Decensor(QtCore.QThread):
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else: #for...else, i.e if the loop finished without encountering break
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print("Corresponding original, uncolored image not found in {}".format(color_file_path))
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print("Check if it exists and is in the PNG or JPG format.")
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self.signals.insertText_progressCursor.emit("Corresponding original, uncolored image not found in {}\n".format(color_file_path))
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self.signals.insertText_progressCursor.emit("Check if it exists and is in the PNG or JPG format.\n")
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#if we are doing a bar decensor
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else:
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self.decensor_image_variations(colored_img, colored_img, file_name)
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else:
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print("--------------------------------------------------------------------------")
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print("Image can't be found: "+str(color_file_path))
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self.signals.insertText_progressCursor.emit("Image can't be found: "+str(color_file_path) + "\n")
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print("--------------------------------------------------------------------------")
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if self.files_removed is not None:
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file.error_messages(None, self.files_removed)
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print("\nDecensoring complete!")
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#unload model to prevent memory issues
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self.signals.update_progress_LABEL.emit("finished", "Decensoring complete! Close this window and reopen DCP to start a new session.")
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# self.signals.update_progress_LABEL.emit("finished", "Decensoring complete! Close this window and reopen DCP to start a new session.")
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self.signals.insertText_progressCursor.emit("\nDecensoring complete! remove decensored file before decensoring again not to overwrite")
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self.signals.update_decensorButton_Enabled.emit(True)
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tf.reset_default_graph()
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def decensor_image_variations(self, ori, colored, file_name=None):
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@ -197,16 +232,25 @@ class Decensor(QtCore.QThread):
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#colored image is only used for finding the regions
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regions = find_regions(colored.convert('RGB'), [v*255 for v in self.mask_color])
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print("Found {region_count} censored regions in this image!".format(region_count = len(regions)))
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self.signals.insertText_progressCursor.emit("Found {region_count} censored regions in this image!".format(region_count = len(regions)))
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if len(regions) == 0 and not self.is_mosaic:
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print("No green regions detected! Make sure you're using exactly the right color.")
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print("No green (0,255,0) regions detected! Make sure you're using exactly the right color.")
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self.signals.insertText_progressCursor.emit("No green (0,255,0) regions detected! Make sure you're using exactly the right color.\n")
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return
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self.signals.signal_ProgressBar_update_MAX_VALUE.emit("Found {} masked regions".format(len(regions)), len(regions))
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# self.signals.signal_ProgressBar_update_MAX_VALUE.emit("Found {} masked regions".format(len(regions)), len(regions))
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print("Found {} masked regions".format(len(regions)))
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# self.signals.insertText_progressCursor.emit("Found {} masked regions\n".format(len(regions)))
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self.signals.update_ProgressBar_MAX_VALUE.emit(len(regions))
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self.signals.update_ProgressBar_SET_VALUE.emit(0)
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output_img_array = ori_array[0].copy()
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for region_counter, region in enumerate(regions, 1):
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self.signals.update_progress_LABEL.emit("\"Decensoring regions in image\"","Decensoring censor {}/{}".format(region_counter,len(regions)))
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# self.signals.update_progress_LABEL.emit("\"Decensoring regions in image\"","Decensoring censor {}/{}".format(region_counter,len(regions)))
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self.signals.insertText_progressCursor.emit("Decensoring regions in image, Decensoring censor {}/{}".format(region_counter,len(regions)))
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bounding_box = expand_bounding(ori, region, expand_factor=1.5)
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crop_img = ori.crop(bounding_box)
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# crop_img.show()
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@ -286,7 +330,9 @@ class Decensor(QtCore.QThread):
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bounding_height_index = row + bounding_box[1]
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if (bounding_width_index, bounding_height_index) in region:
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output_img_array[bounding_height_index][bounding_width_index] = pred_img_array[i,:,:,:][row][col]
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self.signals.signal_ProgressBar_update_VALUE.emit("{} out of {} regions decensored.".format(region_counter, len(regions)), region_counter)
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# self.signals.signal_ProgressBar_update_VALUE.emit("{} out of {} regions decensored.".format(region_counter, len(regions)), region_counter)
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self.signals.update_ProgressBar_SET_VALUE.emit(region_counter)
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self.signals.insertText_progressCursor.emit("{} out of {} regions decensored.\n".format(region_counter, len(regions)))
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print("{region_counter} out of {region_count} regions decensored.".format(region_counter=region_counter, region_count=len(regions)))
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output_img_array = output_img_array * 255.0
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@ -298,7 +344,9 @@ class Decensor(QtCore.QThread):
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output_img = Image.fromarray(output_img_array.astype('uint8'))
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output_img = self.apply_variant(output_img, variant_number)
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self.signals.update_progress_LABEL.emit("current image finished", "Decensoring of current image finished. Saving image...")
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# self.signals.update_progress_LABEL.emit("current image finished", "Decensoring of current image finished. Saving image...")
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self.signals.insertText_progressCursor.emit("Decensoring of current image finished. Saving image...")
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print("current image finished")
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if file_name != None:
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#save the decensored image
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@ -306,10 +354,11 @@ class Decensor(QtCore.QThread):
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file_name = base_name + " " + str(variant_number) + ext
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save_path = os.path.join(self.decensor_output_path, file_name)
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output_img.save(save_path)
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print("Decensored image saved to {save_path}!".format(save_path=save_path))
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return
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self.signals.insertText_progressCursor.emit("Decensored image saved to {save_path}!".format(save_path=save_path))
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self.signals.insertText_progressCursor.emit("="*30)
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else:
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# Legacy Code piece ↓, used when DCPv1 had ui with Painting
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print("Decensored image. Returning it.")
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return output_img
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72
main.py
72
main.py
@ -5,19 +5,27 @@
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# The greater the number of variations, the longer decensoring process will be.
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import sys, time
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from PySide2.QtWidgets import QWidget, QHBoxLayout, QVBoxLayout, QGridLayout, QGroupBox, QDesktopWidget, QApplication, QAction, qApp, QApplication, QMessageBox, QRadioButton, QPushButton, QTextEdit, QLabel, QSizePolicy,QMainWindow
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from PySide2.QtWidgets import QWidget, QHBoxLayout, QVBoxLayout, QGridLayout, QGroupBox, QDesktopWidget, QApplication
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from PySide2.QtWidgets import QAction, qApp, QApplication, QMessageBox, QRadioButton, QPushButton, QTextEdit, QLabel
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from PySide2.QtWidgets import QSizePolicy,QMainWindow, QStatusBar, QProgressBar
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from PySide2.QtCore import Qt, QObject
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from PySide2.QtGui import QFont, QTextCursor
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from decensor import Decensor
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from signals import Signals
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from progressWindow import ProgressWindow
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# from decensor import Decensor
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# from progressWindow import ProgressWindow
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class MainWindow(QWidget):
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def __init__(self):
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super().__init__()
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self.signals = Signals()
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self.initUI()
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self.setSignals()
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self.decensor = Decensor(self)
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self.load_model()
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def initUI(self):
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@ -75,25 +83,60 @@ class MainWindow(QWidget):
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self.progressMessage.setReadOnly(True)
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self.progressCursor.insertText("After you prepared your images, click on the decensor button once to begin decensoring.\nPlease be patient.\nDecensoring will take time.\n")
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# Progress Bar
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self.statusBar = QStatusBar(self)
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self.progressBar = QProgressBar()
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self.progressBar.setMinimum(0)
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self.progressBar.setMaximum(100)
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self.progressBar.setValue(0)
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self.statusLabel = QLabel("Showing Progress")
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self.statusBar.addWidget(self.statusLabel, 1)
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self.statusBar.addWidget(self.progressBar, 2)
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#put all groups into grid
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# addWidget(row, column, rowSpan, columnSpan)
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grid_layout.addWidget(self.tutorialLabel, 0, 0, 1, 2)
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grid_layout.addWidget(self.censorTypeGroupBox, 1, 0, 1, 1)
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grid_layout.addWidget(self.variationsGroupBox, 1, 1, 1, 1)
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grid_layout.addWidget(self.decensorButton, 2, 0, 1, 2)
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grid_layout.addWidget(self.progressMessage, 3, 0, 4, 2)
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grid_layout.addWidget(self.progressMessage, 3, 0, 1, 2)
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grid_layout.addWidget(self.statusBar, 4, 0, 1, 2)
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#window size settings
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self.resize(500, 500)
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self.resize(900, 600)
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self.center()
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self.setWindowTitle('DeepCreamPy v2.2.0-beta')
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self.show()
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def load_model(self):
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# load model to make able to decensor several times
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self.decensorButton.setEnabled(False)
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self.decensorButton.setText("Loading Machine Learning Model (Please Wait...)")
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self.decensor.start()
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self.decensor.signals = self.signals
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self.progressCursor.insertText("Loading Decensor app consumes 6 GB memory at maximum")
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def setSignals(self):
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self.signals.update_decensorButton_Text.connect(self.decensorButton.setText)
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self.signals.update_decensorButton_Enabled.connect(self.decensorButton.setEnabled)
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self.signals.update_statusLabel_Text.connect(self.statusLabel.setText)
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self.signals.update_ProgressBar_SET_VALUE.connect(self.progressBar.setValue)
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self.signals.update_ProgressBar_MAX_VALUE.connect(self.progressBar.setMaximum)
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self.signals.update_ProgressBar_MIN_VALUE.connect(self.progressBar.setMinimum)
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# self.signals.insertText_progressCursor.connect(self.progressCursor.insertText)
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self.signals.insertText_progressCursor.connect(self.progressMessage.append)
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self.signals.clear_progressMessage.connect(self.progressMessage.clear)
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self.signals.appendText_progressMessage.connect(self.progressMessage.append)
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def decensorClicked(self):
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self.decensorButton.setEnabled(False)
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self.progressMessage.clear()
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self.progressCursor.insertText("Decensoring has begun!\n")
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decensor = Decensor(text_edit = self.progressMessage, text_cursor = self.progressCursor, ui_mode = True)
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# for now, decensor is initiated when this app is started
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# self.decensor = Decensor(text_edit = self.progressMessage, text_cursor = self.progressCursor, ui_mode = True)
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#https://stackoverflow.com/questions/42349470/pyqt-find-checked-radiobutton-in-a-group
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#set decensor to right settings
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#censor type
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@ -103,9 +146,9 @@ class MainWindow(QWidget):
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if cb.isChecked():
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censorType = cb.text()
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if censorType == 'Bar censor':
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decensor.is_mosaic = False
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self.decensor.is_mosaic = False
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else:
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decensor.is_mosaic = True
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self.decensor.is_mosaic = True
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#variations count
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variationsElements = self.variationsGroupBox.children()
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@ -113,20 +156,13 @@ class MainWindow(QWidget):
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for vb in variationsButtons:
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if vb.isChecked():
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variations = int(vb.text())
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decensor.variations = variations
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self.decensor.variations = variations
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self.decensorButton.setEnabled(True)
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self.hide()
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self.progress = ProgressWindow(self, decensor = decensor)
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self.decensorButton.setEnabled(False)
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self.decensor.start()
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# decensor.decensor_all_images_in_folder()
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# self.progress.hide()
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# self.show()
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# def showAbout(self):
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# QMessageBox.about(self, 'About', "DeepCreamPy v2.2.0 \n Developed by deeppomf")
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# #centers the main window
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def center(self):
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qr = self.frameGeometry()
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