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https://github.com/Deepshift/DeepCreamPy.git
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Change progress text
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deeppomf
parent
80a2cb8880
commit
d8e113b89c
33
decensor.py
33
decensor.py
@ -65,14 +65,14 @@ class Decensor(QtCore.QThread):
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self.terminate()
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def find_mask(self, colored):
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self.signals.update_progress_LABEL.emit("find_mask()", "finding mask...")
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# self.signals.update_progress_LABEL.emit("find_mask()", "finding mask...")
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mask = np.ones(colored.shape, np.uint8)
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i, j = np.where(np.all(colored[0] == self.mask_color, axis=-1))
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mask[0, i, j] = 0
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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 model...")
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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.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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@ -90,18 +90,18 @@ 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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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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#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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# 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.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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@ -146,6 +146,8 @@ class Decensor(QtCore.QThread):
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self.custom_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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tf.reset_default_graph()
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def decensor_image_variations(self, ori, colored, file_name=None):
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@ -203,11 +205,11 @@ class Decensor(QtCore.QThread):
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self.custom_print("No green regions detected! Make sure you're using exactly the right color.")
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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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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("for-loop, \"for region_counter, region in enumerate(regions, 1):\"","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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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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@ -299,7 +301,7 @@ 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("finished", "decensoring finished, saving as file...")
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self.signals.update_progress_LABEL.emit("current image finished", "Decensoring of current image finished. Saving image...")
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if file_name != None:
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#save the decensored image
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@ -315,14 +317,15 @@ class Decensor(QtCore.QThread):
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return output_img
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def custom_print(self, text):
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if self.ui_mode:
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from PySide2.QtGui import QTextCursor
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print(text)
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# if self.ui_mode:
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# from PySide2.QtGui import QTextCursor
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self.text_cursor.insertText(text)
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self.text_cursor.insertText("\n")
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self.text_edit.moveCursor(QTextCursor.End)
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else:
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print(text)
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# self.text_cursor.insertText(text)
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# self.text_cursor.insertText("\n")
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# self.text_edit.moveCursor(QTextCursor.End)
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# else:
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# print(text)
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# if __name__ == '__main__':
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# decensor = Decensor()
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8
main.py
8
main.py
@ -27,7 +27,7 @@ class MainWindow(QWidget):
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#Tutorial
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self.tutorialLabel = QLabel()
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self.tutorialLabel.setText("Welcome to DeepCreamPy!\n\nIf you're new to DCP, please read the README.\nThis program does nothing without the proper setup of your images.\n\nReport them to me on Github or Twitter @deeppomf.")
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self.tutorialLabel.setText("Welcome to DeepCreamPy!\n\nIf you're new to DCP, please read the README.\nThis program does nothing without the proper setup of your images.\n\nReport any bugs you encounter to me on Github or Twitter @deeppomf.")
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self.tutorialLabel.setAlignment(Qt.AlignCenter)
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self.tutorialLabel.setFont(QFont('Sans Serif', 13))
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@ -85,7 +85,7 @@ class MainWindow(QWidget):
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#window size settings
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self.resize(500, 500)
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self.center()
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self.setWindowTitle('DeepCreamPy v2.2.0-alpha')
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self.setWindowTitle('DeepCreamPy v2.2.0-beta')
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self.show()
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def decensorClicked(self):
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@ -117,10 +117,12 @@ class MainWindow(QWidget):
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self.decensorButton.setEnabled(True)
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# self.hide()
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self.hide()
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self.progress = ProgressWindow(self, decensor = decensor)
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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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