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main.py
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main.py
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import sys
from PyQt5.QtCore import *
from PyQt5.QtGui import *
from PyQt5.QtWidgets import *
import qdarkstyle
import qdarkgraystyle
from time import time
from options.test_options import TestOptions
from ui.ui import Ui_Form
import numpy as np
from sklearn.neighbors import NearestNeighbors
from glob import glob
import cv2
from ui.mouse_event import GraphicsScene
from ui.GT_mouse_event import GTScene
from utils import Build_model
import pickle
from sklearn.manifold import TSNE
from ui.ui import transfer_real_to_slide, invert_slide_to_real, light_transfer_real_to_slide, \
light_invert_slide_to_real, attr_degree_list
import torch
from module.flow import cnf
import os
import tensorflow as tf
from ui.real_time_attr_thread import RealTimeAttrThread
from ui.real_time_light_thread import RealTimeLightThread
# np.random.seed(2)
os.environ["CUDA_VISIBLE_DEVICES"] = "0"
class ExWindow(QMainWindow):
def __init__(self, opt):
super().__init__()
self.EX = Ex(opt)
class Ex(Ui_Form):
real_scene_update = pyqtSignal(bool, name='update_real_scene')
def __init__(self, opt):
super().__init__()
self.lock_mode = False
self.sample_num = 10
self.truncation_psi = 0.5
self.snapshot = 0
self.his_image = []
self.at_intial_point = False
self.keep_indexes = [2, 5, 25, 28, 16, 32, 33, 34, 55, 75, 79, 162, 177, 196, 160, 212, 246, 285, 300, 329, 362,
369, 462, 460, 478, 551, 583, 643, 879, 852, 914, 999, 976, 627, 844, 237, 52, 301,
599]
# self.keep_indexes = [i for i in range(0,100)]
# self.keep_indexes = [0]
self.keep_indexes = np.array(self.keep_indexes).astype(np.int)
self.zero_padding = torch.zeros(1, 18, 1).cuda()
self.real_scene_update.connect(self.update_real_scene)
self.attr_order = ['Gender', 'Glasses', 'Yaw', 'Pitch', 'Baldness', 'Beard', 'Age', 'Expression']
self.lighting_order = ['Left->Right', 'Right->Left', 'Down->Up', 'Up->Down', 'No light', 'Front light']
self.init_deep_model(opt)
self.init_data_points()
self.setupUi(self)
self.show()
self.scene = GraphicsScene(self)
# self.scene.setSceneRect(0, 0, 1024, 1024)
self.graphicsView.setScene(self.scene)
self.graphicsView.setAlignment(Qt.AlignCenter)
self.graphicsView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.graphicsView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.graphicsView.show()
self.lock_scene = GTScene(self)
self.lockView.setScene(self.lock_scene)
self.lockView.setAlignment(Qt.AlignCenter)
self.lockView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.lockView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.lockView.hide()
self.GT_scene = GTScene(self)
self.resultView.setScene(self.GT_scene)
self.resultView.setAlignment(Qt.AlignCenter)
self.resultView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.resultView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.realtime_attr_thread = RealTimeAttrThread(self)
self.realtime_light_thread = RealTimeLightThread(self)
self.init_screen()
def init_deep_model(self, opt):
self.opt = opt
self.model = Build_model(self.opt)
self.w_avg = self.model.Gs.get_var('dlatent_avg')
self.prior = cnf(512, '512-512-512-512-512', 17, 1)
self.prior.load_state_dict(torch.load('flow_weight/modellarge10k.pt'))
self.prior.eval()
def init_screen(self):
self.update_scene_image()
def update_scene_image(self):
qim = QImage(self.map.data, self.map.shape[1], self.map.shape[0], self.map.strides[0],
QImage.Format_RGB888)
pixmap = QPixmap.fromImage(qim)
self.scene.reset()
if len(self.scene.items()) > 0:
self.scene.reset_items()
self.scene.addPixmap(pixmap)
def update_GT_scene_image(self):
self.at_intial_point = True
# self.scene.pickedImageIndex = 28
self.w_current = self.all_w[self.scene.pickedImageIndex].copy()
self.attr_current = self.all_attr[self.scene.pickedImageIndex].copy()
self.light_current = self.all_lights[self.scene.pickedImageIndex].copy()
self.attr_current_list = [self.attr_current[i][0] for i in range(len(self.attr_order))]
self.light_current_list = [0 for i in range(len(self.lighting_order))]
for i, j in enumerate(self.attr_order):
self.slider_list[i].setValue(transfer_real_to_slide(j, self.attr_current_list[i]))
for i, j in enumerate(self.lighting_order):
self.lighting_slider_list[i].setValue(0)
################################ calculate attributes array first, then change the values of attributes
self.q_array = torch.from_numpy(self.w_current).cuda().clone().detach()
self.array_source = torch.from_numpy(self.attr_current).type(torch.FloatTensor).cuda()
self.array_light = torch.from_numpy(self.light_current).type(torch.FloatTensor).cuda()
self.pre_lighting_distance = [self.pre_lighting[i] - self.array_light for i in range(len(self.lighting_order))]
self.final_array_source = torch.cat([self.array_light, self.array_source.unsqueeze(0).unsqueeze(-1)], dim=1)
self.final_array_target = torch.cat([self.array_light, self.array_source.unsqueeze(0).unsqueeze(-1)], dim=1)
# print(self.q_array.shape, self.final_array_source.shape, self.zero_padding.shape)
self.fws = self.prior(self.q_array, self.final_array_source, self.zero_padding)
self.GAN_image = self.model.generate_im_from_w_space(self.w_current)[0]
qim = QImage(self.GAN_image.data, self.GAN_image.shape[1], self.GAN_image.shape[0], self.GAN_image.strides[0],
QImage.Format_RGB888)
showedImagePixmap = QPixmap.fromImage(qim)
# showedImagePixmap = showedImagePixmap.scaled(QSize(256, 256), Qt.IgnoreAspectRatio)
self.GT_scene.reset()
if len(self.GT_scene.items()) > 0:
self.GT_scene.reset_items()
self.lock_scene.reset()
if len(self.lock_scene.items()) > 0:
self.lock_scene.reset_items()
self.GT_scene.addPixmap(showedImagePixmap)
self.lock_scene.addPixmap(showedImagePixmap)
for i in range(15):
self.style_button_list[i].setIcon(QIcon())
self.style_button_list[0].setIcon(QIcon(showedImagePixmap.scaled(128, 128)))
self.his_image = []
self.his_image.append(qim.copy())
self.at_intial_point = False
def update_lock_scene(self):
qim = QImage(self.GAN_image.data, self.GAN_image.shape[1], self.GAN_image.shape[0], self.GAN_image.strides[0],
QImage.Format_RGB888)
showedImagePixmap = QPixmap.fromImage(qim)
if len(self.lock_scene.items()) > 0:
self.lock_scene.reset_items()
self.lock_scene.addPixmap(showedImagePixmap)
self.snapshot += 1
self.style_button_list[self.snapshot].setIcon(QIcon(showedImagePixmap.scaled(128, 128)))
self.his_image.append(qim.copy())
def update_real_scene(self):
qim = QImage(self.GAN_image.data, self.GAN_image.shape[1], self.GAN_image.shape[0], self.GAN_image.strides[0],
QImage.Format_RGB888)
showedImagePixmap = QPixmap.fromImage(qim)
self.GT_scene.addPixmap(showedImagePixmap)
def show_his_image(self, i):
qim = self.his_image[i]
showedImagePixmap = QPixmap.fromImage(qim)
if len(self.lock_scene.items()) > 0:
self.lock_scene.reset_items()
self.lock_scene.addPixmap(showedImagePixmap)
def real_time_editing_thread(self, attr_index, raw_slide_value):
self.realtime_attr_thread.render(attr_index, raw_slide_value, tf.get_default_session())
def real_time_light_thread(self, light_index, raw_slide_value):
self.realtime_light_thread.render(light_index, raw_slide_value, tf.get_default_session())
def real_time_lighting(self, light_index, raw_slide_value):
if not self.at_intial_point:
real_value = light_invert_slide_to_real(self.lighting_order[light_index], raw_slide_value)
self.light_current_list[light_index] = real_value
###############################
############### calculate attributes array first, then change the values of attributes
lighting_final = self.array_light.clone().detach()
for i in range(len(self.lighting_order)):
lighting_final += self.light_current_list[i] * self.pre_lighting_distance[i]
self.final_array_target[:, :9] = lighting_final
self.rev = self.prior(self.fws[0], self.final_array_target, self.zero_padding, True)
self.rev[0][0][0:7] = self.q_array[0][0:7]
self.rev[0][0][12:18] = self.q_array[0][12:18]
self.w_current = self.rev[0].detach().cpu().numpy()
self.q_array = torch.from_numpy(self.w_current).cuda().clone().detach()
self.fws = self.prior(self.q_array, self.final_array_target, self.zero_padding)
self.GAN_image = self.model.generate_im_from_w_space(self.w_current)[0]
else:
pass
def real_time_editing(self, attr_index, raw_slide_value):
if not self.at_intial_point:
real_value = invert_slide_to_real(self.attr_order[attr_index], raw_slide_value)
attr_change = real_value - self.attr_current_list[attr_index]
attr_final = attr_degree_list[attr_index] * attr_change + self.attr_current_list[attr_index]
self.final_array_target[0, attr_index + 9, 0, 0] = attr_final
self.rev = self.prior(self.fws[0], self.final_array_target, self.zero_padding, True)
if attr_index == 0:
self.rev[0][0][8:] = self.q_array[0][8:]
elif attr_index == 1:
self.rev[0][0][:2] = self.q_array[0][:2]
self.rev[0][0][4:] = self.q_array[0][4:]
elif attr_index == 2:
self.rev[0][0][4:] = self.q_array[0][4:]
elif attr_index == 3:
self.rev[0][0][4:] = self.q_array[0][4:]
elif attr_index == 4:
self.rev[0][0][6:] = self.q_array[0][6:]
elif attr_index == 5:
self.rev[0][0][:5] = self.q_array[0][:5]
self.rev[0][0][10:] = self.q_array[0][10:]
elif attr_index == 6:
self.rev[0][0][0:4] = self.q_array[0][0:4]
self.rev[0][0][8:] = self.q_array[0][8:]
elif attr_index == 7:
self.rev[0][0][:4] = self.q_array[0][:4]
self.rev[0][0][6:] = self.q_array[0][6:]
self.w_current = self.rev[0].detach().cpu().numpy()
self.q_array = torch.from_numpy(self.w_current).cuda().clone().detach()
self.fws = self.prior(self.q_array, self.final_array_target, self.zero_padding)
self.GAN_image = self.model.generate_im_from_w_space(self.w_current)[0]
else:
pass
def reset_Wspace(self):
self.update_GT_scene_image()
def init_data_points(self):
self.raw_w = pickle.load(open("data/sg2latents.pickle", "rb"))
self.raw_TSNE = np.load('data/TSNE.npy')
self.raw_attr = np.load('data/attributes.npy')
self.raw_lights2 = np.load('data/light.npy')
self.raw_lights = self.raw_lights2
self.all_w = np.array(self.raw_w['Latent'])[self.keep_indexes]
self.all_attr = self.raw_attr[self.keep_indexes]
self.all_lights = self.raw_lights[self.keep_indexes]
light0 = torch.from_numpy(self.raw_lights2[8]).type(torch.FloatTensor).cuda()
light1 = torch.from_numpy(self.raw_lights2[33]).type(torch.FloatTensor).cuda()
light2 = torch.from_numpy(self.raw_lights2[641]).type(torch.FloatTensor).cuda()
light3 = torch.from_numpy(self.raw_lights2[547]).type(torch.FloatTensor).cuda()
light4 = torch.from_numpy(self.raw_lights2[28]).type(torch.FloatTensor).cuda()
light5 = torch.from_numpy(self.raw_lights2[34]).type(torch.FloatTensor).cuda()
self.pre_lighting = [light0, light1, light2, light3, light4, light5]
self.X_samples = self.raw_TSNE[self.keep_indexes]
self.map = np.ones([1024, 1024, 3], np.uint8) * 255
for point in self.X_samples:
######### don't use np.uint8 in tuple((point*1024).astype(int))
cv2.circle(self.map, tuple((point * 1024).astype(int)), 6, (0, 0, 255), -1)
self.nbrs = NearestNeighbors(n_neighbors=1, algorithm='ball_tree').fit(self.X_samples)
@pyqtSlot()
def lock_switch(self):
self.lock_mode = not self.lock_mode
if self.lock_mode:
self.brushButton.setStyleSheet("background-color:")
self.lockView.show()
self.graphicsView.hide()
else:
self.brushButton.setStyleSheet("background-color:")
self.brushButton.setStyleSheet("background-color: #85adad")
self.graphicsView.show()
self.lockView.hide()
if __name__ == '__main__':
opt = TestOptions().parse()
app = QApplication(sys.argv)
# app.setStyleSheet(qdarkgraystyle.load_stylesheet())
app.setStyleSheet(qdarkstyle.load_stylesheet_pyqt5())
ex = ExWindow(opt)
# ex = Ex(opt)
sys.exit(app.exec_())