def gen_jpg_tga(file_='', work_="", dds_list=None):
try:
if dds_list is None:
dds_list = []
# f = open(file_, "r", encoding='utf-8-sig')
# f.readline()
for file in dds_list:
file = file.replace("\n", "")
low_file = file.lower()
if low_file.find('_mre') > -1 or low_file.find('_nor') > -1:
continue
# 实例化
# file = file.replace("\n", "")
a = PathUtils(_work=work_, dds_path=file)
file_real_path = a.real_dds_path()
# file_real_path = work_ + file
if os.path.exists(file_real_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append(f"{file_real_path} 不存在")
continue
jpg_path, tga_path = a.dds_to_jpg_path(), a.dds_to_tga_path()
if os.path.exists(os.path.dirname(jpg_path)) is False:
os.makedirs(os.path.dirname(jpg_path))
if os.path.exists(jpg_path) is False:
main_cmd = f"{exe_dir} \"{file_real_path}\" \"{jpg_path}\" \"{tga_path}\""
main_cmd = main_cmd.replace("\n", "")
print(main_cmd)
# do real job
os.system(main_cmd)
else:
print(jpg_path + ' 已存在，跳过')
except BaseException as e:
print(e)
def save_all(self):
GlobalConfig.b_sync_block_op_in_progress = True
QApplication.processEvents()
InfoNotifier.InfoNotifier.g_progress_info.append(
"开始保存图片··············")
# gen_style_batch3.style_main3(self.content_list,self.chosen_style_pic)
style_transfer.style_main(self.content_list, self.chosen_style_pic,
self.project_base, False)
for file in self.content_list:
file_name = os.path.basename(file)
get_path = PathUtils(self.project_base, self.chosen_style_pic,
file)
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
# lerp
style_out_pic_path = get_path.get_style_path()
if os.path.exists(style_out_pic_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append(
f"不存在对应风格化图片{style_out_pic_path}。跳过本张图片")
continue
lerp_out_path = get_path.get_jpg_lerp_path()
if os.path.exists(os.path.dirname(lerp_out_path)) is False:
os.makedirs(os.path.dirname(lerp_out_path))
lerp_ret, _ = gen_lerp_ret.lerp_img(jpg_path, style_out_pic_path,
self.lerg_value)
gen_lerp_ret.write_img(lerp_ret, lerp_out_path)
# combine alpha c
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_out_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_out_path = lerp_out_path.replace(".jpg", ".tga")
tga_img.save(lerp_out_path, quality=100)
print(f"generate tga image {lerp_out_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append(
f"生成插值操作后的tga图片: {lerp_out_path} ")
# dds
# 图片目录路径
dds_out = get_path.get_dds_output_path()
if os.path.exists(dds_out) is False:
os.makedirs(dds_out)
main_cmd = f"{self.texconv_path} -dxt5 -file {lerp_out_path} -outdir {dds_out}"
main_cmd.replace("\n", "")
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append('生成DDS贴图：' +
dds_out +
file_name)
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
GlobalConfig.b_sync_block_op_in_progress = False
self._signal.emit()
def gen_expanded_pic(self):
InfoNotifier.InfoNotifier.g_progress_info.append("开始生成DDS贴图············")
GlobalConfig.b_sync_block_op_in_progress = True
QApplication.processEvents()
pad = 256
# 存放被选中的目录中图片的相对路径到pic_list中
pic_list = []
for file in self.chosen_content_file_list:
file_path = self.file_dict[file]
tmp = glob.glob(self.project_base + '/' + file_path + '/*.dds')
for i in range(len(tmp)):
tmp[i] = tmp[i].replace(self.project_base + '/', "")
pic_list += tmp
# 遍历文件目录
for file in pic_list:
# 当前文件名
get_path = PathUtils(self.project_base, self.chosen_style_pic, file)
expanded_jpg = get_path.get_expanded_jpg_path()
expanded_tga = get_path.get_expanded_tga_path()
if os.path.exists(expanded_jpg) is False:
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
# expand
img_jpg = Image.open(jpg_path)
img_tga = Image.open(tga_path)
width = img_jpg.width
height = img_jpg.height
assert width == img_tga.width and height == img_tga.height
img_jpg_pad = Image.new("RGB", (width * 3, height * 3))
img_tga_pad = Image.new("RGBA", (width * 3, height * 3))
for i in range(3):
for j in range(3):
img_jpg_pad.paste(img_jpg, (i * width, j * height, (i + 1) * width, (j + 1) * height))
img_tga_pad.paste(img_tga, (i * width, j * height, (i + 1) * width, (j + 1) * height))
img_jpg_crop = img_jpg_pad.crop((width - pad, height - pad, 2 * width + pad, 2 * height + pad))
if os.path.exists(os.path.dirname(expanded_jpg)) is False:
os.makedirs(os.path.dirname(expanded_jpg))
img_jpg_crop.save(expanded_jpg, quality=100)
print(expanded_jpg)
img_tga_crop = img_tga_pad.crop((width - pad, height - pad, 2 * width + pad, 2 * height + pad))
img_tga_crop.save(expanded_tga, quality=100)
print(expanded_tga)
InfoNotifier.InfoNotifier.g_progress_info.append(
f'保存expand后图片：{expanded_tga}，jpg')
else:
InfoNotifier.InfoNotifier.g_progress_info.append(expanded_tga + ' exists')
def gen_lerg(self, pic_list):
InfoNotifier.InfoNotifier.g_progress_info.append("开始生成DDS贴图···········")
for file_path in pic_list:
file_name = os.path.basename(file_path)
get_path = PathUtils(self.project_base, self.chosen_style_pic, file_path)
# 原图
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
# 风格后图片
style_real_path = get_path.get_style_path()
# 待保存-lerg
lerp_real_path = get_path.get_jpg_lerp_path()
# 待保存-dds
dds_real_path = get_path.get_dds_output_path()
#######################################################
if os.path.exists(jpg_path) is False:
print("dds not transfered")
continue
if os.path.exists(style_real_path) is False:
print('img not stylized')
continue
if os.path.exists(os.path.dirname(lerp_real_path)) is False:
os.makedirs(os.path.dirname(lerp_real_path))
if os.path.exists(dds_real_path) is False:
os.makedirs(dds_real_path)
try:
lerp_ret, ret = gen_lerp_ret.lerp_img(jpg_path, style_real_path, self.lerp_value)
gen_lerp_ret.write_img(lerp_ret, lerp_real_path)
except BaseException as be:
print(be)
# combine alpha channel
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_real_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_real_path = lerp_real_path.replace(".jpg", ".tga")
tga_img.save(lerp_real_path, quality=100)
print(f"generate tga image {lerp_real_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append(f"生成插值操作后的tga图片 {lerp_real_path} ")
# dds
main_cmd = f"{self.texconv_path} -dxt5 -file {lerp_real_path} -outdir {dds_real_path}"
main_cmd.replace("\n", "")
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append(f'将{dds_real_path}{file_name}转化为DDS格式···')
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
def expanded(self):
InfoNotifier.InfoNotifier.g_progress_info.append(
"开始保存图片··············")
GlobalConfig.b_sync_block_op_in_progress = True
QApplication.processEvents()
pad = 256
for file in self.content_list:
get_path = PathUtils(self.project_base, self.chosen_style_pic,
file)
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
expanded_jpg = get_path.get_expanded_jpg_path()
expanded_tga = get_path.get_expanded_tga_path()
# expand
img_jpg = Image.open(jpg_path)
img_tga = Image.open(tga_path)
width = img_jpg.width
height = img_jpg.height
assert width == img_tga.width and height == img_tga.height
img_jpg_pad = Image.new("RGB", (width * 3, height * 3))
img_tga_pad = Image.new("RGBA", (width * 3, height * 3))
for i in range(3):
for j in range(3):
img_jpg_pad.paste(img_jpg,
(i * width, j * height, (i + 1) * width,
(j + 1) * height))
img_tga_pad.paste(img_tga,
(i * width, j * height, (i + 1) * width,
(j + 1) * height))
img_jpg_crop = img_jpg_pad.crop(
(width - pad, height - pad, 2 * width + pad, 2 * height + pad))
if os.path.exists(os.path.dirname(expanded_jpg)) is False:
os.makedirs(os.path.dirname(expanded_jpg))
img_jpg_crop.save(expanded_jpg, quality=100)
print(expanded_jpg)
img_tga_crop = img_tga_pad.crop(
(width - pad, height - pad, 2 * width + pad, 2 * height + pad))
img_tga_crop.save(expanded_tga, quality=100)
print(expanded_tga)
InfoNotifier.InfoNotifier.g_progress_info.append(
f'保存expand后图片：{expanded_jpg}，jpg')
def gen_lerp_pic(self):
try:
file_list = self.chosen_content_file_list
# 存放被选中的目录中图片的相对路径
pic_list = []
for file in file_list:
file_path = self.file_dict[file]
tmp = glob.glob(self.project_base + '/' + file_path + '/*.dds')
for i in range(len(tmp)):
tmp[i] = tmp[i].replace(self.project_base + '/', "")
pic_list += tmp
for file in pic_list:
file_name = os.path.basename(file)
get_path = PathUtils(self.project_base, self.chosen_style_pic, file)
jpg_path = get_path.get_expanded_jpg_path()
tga_path = get_path.get_expanded_tga_path()
tmp_style_in = jpg_path
# lerp
style_out_pic_path = get_path.get_expanded_style_path()
if os.path.exists(style_out_pic_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append("不存在对应风格化图片。跳过本张图片")
continue
lerp_out_path = get_path.get_expanded_lerp_path_jpg()
if os.path.exists(os.path.dirname(lerp_out_path)) is False:
os.makedirs(os.path.dirname(lerp_out_path))
lerp_ret, _ = gen_lerp_ret.lerp_img(tmp_style_in, style_out_pic_path, self.lerp_value)
gen_lerp_ret.write_img(lerp_ret, lerp_out_path)
# combine alpha c
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_out_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_out_path = lerp_out_path.replace(".jpg", ".tga")
tga_img.save(lerp_out_path, quality=100)
print(f"generate tga image {lerp_out_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append('生成插值操作后的tga图片' + lerp_out_path)
# seamless
seamless_path = os.path.dirname(get_path.get_seamless_path())
if os.path.exists(seamless_path) is False:
os.makedirs(seamless_path)
# print("seamless:"+PathUtils.get_expanded_lerp_path_tga())
img = Image.open(get_path.get_expanded_lerp_path_tga())
width = img.width
height = img.height
pad = 256
img_crop = img.crop((pad, pad, width - pad, height - pad))
img_crop.save(get_path.get_seamless_path(), quality=100)
InfoNotifier.InfoNotifier.g_progress_info.append('生成无缝贴图' + get_path.get_seamless_path())
# dds
dds_output = get_path.get_dds_output_path()
if os.path.exists(dds_output) is False:
os.makedirs(dds_output)
main_cmd = f"{self.texconv_path} -dxt5 -file {get_path.get_seamless_path()} -outdir {dds_output}"
main_cmd.replace("\n", "")
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append(f'将{dds_output}{file_name}转化为DDS格式···')
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
# InfoNotifier.InfoNotifier.g_progress_info.append("dds图片已转化完毕")
except BaseException as be:
print(be)
def save_all(self):
# gen_seamless_style_batch3.style_main3(self.content_list,self.chosen_style_pic)
style_transfer.style_main(self.content_list, self.chosen_style_pic,
self.project_base, True)
for file in self.content_list:
file = file.replace("\n", "")
file_name = os.path.basename(file)
get_path = PathUtils(self.project_base, self.chosen_style_pic,
file)
jpg_path = get_path.get_expanded_jpg_path()
tga_path = get_path.get_expanded_tga_path()
tmp_style_in = jpg_path
# lerp
style_out_pic_path = get_path.get_expanded_style_path()
if os.path.exists(style_out_pic_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append(
f"不存在对应风格化图片{style_out_pic_path}。跳过本张图片")
continue
lerp_out_path = get_path.get_expanded_lerp_path_jpg()
if os.path.exists(os.path.dirname(lerp_out_path)) is False:
os.makedirs(os.path.dirname(lerp_out_path))
lerp_ret, _ = gen_lerp_ret.lerp_img(tmp_style_in,
style_out_pic_path,
self.lerg_value)
gen_lerp_ret.write_img(lerp_ret, lerp_out_path)
# combine alpha c
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_out_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_out_path = lerp_out_path.replace(".jpg", ".tga")
tga_img.save(lerp_out_path, quality=100)
print(f"generate tga image {lerp_out_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append(
f"生成插值操作后的tga图片 {lerp_out_path} ")
# seamless
seamless_path = get_path.get_seamless_path()
if os.path.exists(os.path.dirname(seamless_path)) is False:
os.makedirs(os.path.dirname(seamless_path))
img = Image.open(get_path.get_expanded_tga_path())
width = img.width
height = img.height
pad = 256
img_crop = img.crop((pad, pad, width - pad, height - pad))
img_crop.save(seamless_path, quality=100)
InfoNotifier.InfoNotifier.g_progress_info.append("生成无缝贴图：" +
seamless_path)
dds_output = get_path.get_dds_output_path()
if os.path.exists(dds_output) is False:
os.makedirs(dds_output)
main_cmd = f"{self.texconv_path} -dxt5 -file {seamless_path} -outdir {dds_output}"
main_cmd.replace("\n", "")
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append('生成DDS贴图：' +
dds_output +
file_name)
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
GlobalConfig.b_sync_block_op_in_progress = False
self._signal.emit()
def save_all(self):
f = open(self.txt_path, "r", encoding='utf-8-sig')
style_transfer.style_main_txt(self.txt_path, self.work_, self.chosen_style_pic,
self.chosen_content_file_list, self.dir_dict, True)
# gen_style_seamless_txt.style_txt_main2(self.txt_path,self.work_,self.chosen_style_pic,self.chosen_content_file_list,self.dir_dict)
# gen_style_class.style_txt_main2(self.txt_path,self.work_,self.chosen_style_pic,self.chosen_content_file_list,self.dir_dict,True)
for file in f:
file = file.replace("\n", "").replace("\\", "/")
# 判断该图片是否在选中目录中
flag = False
for sub_file in self.chosen_content_file_list:
if self.dir_dict[sub_file] == os.path.dirname(file):
flag = True
break
if flag is True:
get_path = PathUtils(self.work_, self.chosen_style_pic, file, self.txt_path)
file_real_path = get_path.real_dds_path()
file_name = os.path.basename(file_real_path)
jpg_path = get_path.get_expanded_jpg_path()
tga_path = get_path.get_expanded_tga_path()
tmp_style_in = jpg_path
# lerp
style_out_pic_path = get_path.get_expanded_style_path()
if os.path.exists(style_out_pic_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append("不存在对应风格化图片。跳过本张图片")
continue
lerp_out_path = get_path.get_expanded_lerp_path_jpg()
if os.path.exists(os.path.dirname(lerp_out_path)) is False:
os.makedirs(os.path.dirname(lerp_out_path))
lerp_ret, _ = gen_lerp_ret.lerp_img(tmp_style_in, style_out_pic_path, self.lerg_value)
gen_lerp_ret.write_img(lerp_ret, lerp_out_path)
# combine alpha c
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_out_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_out_path = lerp_out_path.replace(".jpg", ".tga")
tga_img.save(lerp_out_path, quality=100)
print(f"generate tga image {lerp_out_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append('生成插值操作后的tga图片' + lerp_out_path)
# seamless
seamless_path = os.path.dirname(get_path.get_seamless_path())
if os.path.exists(seamless_path) is False:
os.makedirs(seamless_path)
# print("seamless:"+PathUtils.get_expanded_lerp_path_tga())
img = Image.open(get_path.get_expanded_lerp_path_tga())
width = img.width
height = img.height
pad = 256
img_crop = img.crop((pad, pad, width - pad, height - pad))
img_crop.save(get_path.get_seamless_path(), quality=100)
InfoNotifier.InfoNotifier.g_progress_info.append('生成无缝贴图' + get_path.get_seamless_path())
# dds_output = get_path.get_seamless_dds_path()
dds_output = get_path.get_dds_output_path_txt()
if os.path.exists(dds_output) is False:
os.makedirs(dds_output)
main_cmd = f"{self.texconv_path} -dxt5 -file {get_path.get_seamless_path()} -outdir {dds_output}"
main_cmd.replace("\n", "")
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append(f'将{dds_output}{file_name}转化为DDS格式···')
self.path_dic.set_src_dst_path_to_map(file, get_path.get_relative_dds_output_path())
self.path_dic.serilize_to_file(get_path.work_output, get_path.get_txt_name(), get_path.get_style_name())
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
GlobalConfig.b_sync_block_op_in_progress = False
self._signal.emit()
def expanded(self):
GlobalConfig.b_sync_block_op_in_progress = True
QApplication.processEvents()
pad = 256
f = open(self.txt_path, "r", encoding='utf-8-sig')
for file in f:
file = file.replace("\n", "").replace("\\", "/")
get_path = PathUtils(self.work_, self.chosen_style_pic, file)
# 判断该图片是否在选中目录中
flag = False
for sub_file in self.chosen_content_file_list:
if self.dir_dict[sub_file] == os.path.dirname(file):
flag = True
break
if flag is True:
if os.path.exists(get_path.get_expanded_tga_path()) is False:
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
# expand
img_jpg = Image.open(jpg_path)
img_tga = Image.open(tga_path)
width = img_jpg.width
height = img_jpg.height
assert width == img_tga.width and height == img_tga.height
img_jpg_pad = Image.new("RGB", (width * 3, height * 3))
img_tga_pad = Image.new("RGBA", (width * 3, height * 3))
for i in range(3):
for j in range(3):
img_jpg_pad.paste(img_jpg, (i * width, j * height, (i + 1) * width, (j + 1) * height))
img_tga_pad.paste(img_tga, (i * width, j * height, (i + 1) * width, (j + 1) * height))
img_jpg_crop = img_jpg_pad.crop((width - pad, height - pad, 2 * width + pad, 2 * height + pad))
if os.path.exists(os.path.dirname(get_path.get_expanded_jpg_path())) is False:
os.makedirs(os.path.dirname(get_path.get_expanded_jpg_path()))
img_jpg_crop.save(get_path.get_expanded_jpg_path(), quality=100)
print(get_path.get_expanded_jpg_path())
img_tga_crop = img_tga_pad.crop((width - pad, height - pad, 2 * width + pad, 2 * height + pad))
img_tga_crop.save(get_path.get_expanded_tga_path(), quality=100)
print(get_path.get_expanded_tga_path())
InfoNotifier.InfoNotifier.g_progress_info.append(
f'保存expand后图片：{get_path.get_expanded_tga_path()}，jpg')
else:
InfoNotifier.InfoNotifier.g_progress_info.append(get_path.get_expanded_tga_path() + ' 已存在，跳过')
def save_all(self):
GlobalConfig.b_sync_block_op_in_progress = True
QApplication.processEvents()
f = open(self.txt_path, "r", encoding='utf-8-sig')
style_transfer.style_main_txt(self.txt_path, self.work_, self.chosen_style_pic, self.chosen_content_file_list,
self.dir_dict, False)
# style_txt_main2(self.txt_path,self.work_,self.chosen_style_pic,self.chosen_content_file_list,self.dir_dict)
for file in f:
file = file.replace("\n", "").replace("\\", "/")
# 判断该图片是否在选中目录中
flag = False
for sub_file in self.chosen_content_file_list:
if self.dir_dict[sub_file] == os.path.dirname(file):
flag = True
break
if flag is True:
# file_real_path=self.work_+'/'+file
# file_name = os.path.basename(file)
get_path = PathUtils(_work=self.work_, _style_path=self.chosen_style_pic, dds_path=file,
txt_file_=self.txt_path)
jpg_path = get_path.dds_to_jpg_path()
tga_path = get_path.dds_to_tga_path()
# lerp
style_out_pic_path = get_path.get_style_path()
if os.path.exists(style_out_pic_path) is False:
InfoNotifier.InfoNotifier.g_progress_info.append(f"不存在对应风格化图片{style_out_pic_path}。跳过本张图片")
continue
lerp_out_path = get_path.get_jpg_lerp_path()
if os.path.exists(os.path.dirname(lerp_out_path)) is False:
os.makedirs(os.path.dirname(lerp_out_path))
# 原图不存在则跳过
if os.path.exists(jpg_path) is False:
print(jpg_path + " is not exist!")
continue
lerp_ret, _ = gen_lerp_ret.lerp_img(jpg_path, style_out_pic_path, self.lerg_value)
gen_lerp_ret.write_img(lerp_ret, lerp_out_path)
# combine alpha c
tga_img = Image.open(tga_path)
jpg_img = Image.open(lerp_out_path)
ir_tmp, ig_tmp, ib_tmp, ia = tga_img.split()
ir, ig, ib = jpg_img.split()
tga_img = Image.merge('RGBA', (ir, ig, ib, ia))
lerp_out_path = lerp_out_path.replace(".jpg", ".tga")
tga_img.save(lerp_out_path, quality=100)
print(f"generate tga image {lerp_out_path} after lerp op.")
InfoNotifier.InfoNotifier.g_progress_info.append(f"生成插值操作后的tga图片{lerp_out_path} ")
dds_out = get_path.get_dds_output_path_txt()
if os.path.exists(dds_out) is False:
os.makedirs(dds_out)
main_cmd = f"{self.texconv_path} -dxt5 -file {lerp_out_path} -outdir {dds_out}"
main_cmd.replace("\n", "")
try:
os.system(main_cmd)
InfoNotifier.InfoNotifier.g_progress_info.append(f"将{lerp_out_path}转化为DDS格式···")
except BaseException as bec:
InfoNotifier.InfoNotifier.g_progress_info.append(bec)
self.path_dic.set_src_dst_path_to_map(file, get_path.get_relative_dds_output_path())
self.path_dic.serilize_to_file(get_path.work_output, get_path.get_txt_name(), get_path.get_style_name())
InfoNotifier.InfoNotifier.g_progress_info.append("保存完成")
GlobalConfig.b_sync_block_op_in_progress = False
self._signal.emit()
def style_main_txt(txt_path='',
work_='',
style_dir='',
chosen_content_file_list=None,
dir_dict=None,
seamless=False):
e_used = False
if chosen_content_file_list is None:
chosen_content_file_list = []
if dir_dict is None:
dir_dict = {}
if os.path.exists(txt_path) is not None:
# content_name=pics_dir[0].replace("\\","/").split("/")[-2]
# set device on GPU if available, else CPU
device = Device()
# set model
d = load_model(device)
s = Image.open(style_dir)
s_tensor = trans(s).unsqueeze(0).to(device)
# read txt
# style_name=os.path.basename(style_dir).split('.')[0]
f = open(txt_path, "r", encoding='utf-8-sig')
for file_path in f:
file_path = file_path.replace("\n", "").replace("\\", "/")
flag = False
# 判断该图片是否在选中目录中
for file in chosen_content_file_list:
if dir_dict[file] == os.path.dirname(file_path):
flag = True
break
if flag is True:
# file_path=file_path.replace("\n","")
# file_name=os.path.basename(file_path)
# file_path=work_+'/'+file_path
# parent_path=os.path.dirname(file_path)
get_path = PathUtils(work_, style_dir, file_path)
# get_path.work_ = work_
# get_path.style_path = style_dir
# get_path.dds_path=file_path
if seamless is False:
jpg_path = get_path.dds_to_jpg_path()
else:
jpg_path = get_path.get_expanded_jpg_path()
# jpg_path=parent_path+'/style_transfer/'+file_name.replace(".dds",".jpg")
if os.path.exists(jpg_path) is False:
print(jpg_path + "is not exist,jump from process")
continue
if seamless is False:
style_output_path = get_path.get_style_path()
else:
style_output_path = get_path.get_expanded_style_path()
style_outdir = os.path.dirname(
os.path.dirname(style_output_path))
if os.path.exists(style_outdir) is False:
os.makedirs(style_outdir)
if jpg_path.endswith(".jpg") is False:
continue
try:
# 文件名
# # file = os.path.basename(jpg_path)
# c_name = os.path.splitext(os.path.basename(jpg_path))[0]
# s_name = os.path.splitext(os.path.basename(style_dir))[0]
file, c_name = get_c_name_and_file_name(jpg_path)
s_name = get_style_name(style_dir)
if os.path.exists(style_output_path) is False:
# if os.path.exists(f'{style_outdir}{s_name}/' + file) is False:
e = VGGEncoder().to(device)
e_used = True
tar = get_target_img(jpg_path,
device,
e,
d,
s_tensor,
c_name,
s_name,
style_outdir=style_outdir)
else:
print("file exists")
InfoNotifier.InfoNotifier.g_progress_info.append(
style_output_path + '已存在，跳过')
except RuntimeError:
print(
'Images are too large to transfer. Size under 1000 are recommended '
+ file_path)
InfoNotifier.InfoNotifier.g_progress_info.append(
f"{file_path}太大，无法迁移风格，推荐尝试1000×1000以下图片")
try:
if os.path.exists(style_output_path) is False:
# save style transfer result
if os.path.exists(
os.path.dirname(style_output_path)) is False:
os.makedirs(os.path.dirname(style_output_path))
tar.save(style_output_path, quality=100)
print(f'result saved into files {style_output_path}/')
InfoNotifier.InfoNotifier.g_progress_info.append(
f'风格图保存到: {style_output_path}')
else:
print("exists")
except BaseException as ec:
print(ec)
InfoNotifier.InfoNotifier.g_progress_info.append(
'error when saving stylized image')
try:
if e_used is True:
del e
except RuntimeError:
pass
def style_main(pics_dir=None, style_dir='', base_dir='', seamless=False):
e_used = False
if pics_dir is None:
pics_dir = []
s_name = os.path.splitext(os.path.basename(style_dir))[0]
if pics_dir is not None:
# content_name=pics_dir[0].replace("\\","/").split("/")[-2]
# set device on GPU if available, else CPU
# 判断是否存在预览图，若都已存在则不加载模型
flag = True
for pic_dir in pics_dir:
if os.path.exists(
f'{os.path.dirname(pic_dir)}/temp/{s_name}/{os.path.basename(pic_dir)}'
) is False:
flag = False
break
if flag is False:
device = Device()
# set model
d = load_model(device)
s = Image.open(style_dir)
s_tensor = trans(s).unsqueeze(0).to(device)
for file_path in pics_dir:
file_path.replace("\\", "/")
get_path = PathUtils(base_dir, style_dir, file_path)
if seamless is False:
jpg_path = get_path.dds_to_jpg_path()
style_output = get_path.get_style_path()
else:
jpg_path = get_path.get_expanded_jpg_path()
style_output = get_path.get_expanded_style_path()
save_dir = os.path.dirname(os.path.dirname(style_output))
if os.path.exists(save_dir) is False:
os.makedirs(save_dir)
if os.path.exists(jpg_path) is False:
print(jpg_path + "is not exist,jump from process")
continue
if jpg_path.endswith(".jpg") is False:
continue
try:
# 文件名
# file=os.path.basename(jpg_path)
# c_name = os.path.splitext(os.path.basename(jpg_path))[0]
# s_name = os.path.splitext(os.path.basename(style_dir))[0]
file, c_name = get_c_name_and_file_name(jpg_path)
s_name = get_style_name(style_dir)
print(s_name)
if os.path.exists(style_output) is False:
e = VGGEncoder().to(device)
e_used = True
tar = get_target_img(jpg_path,
device,
e,
d,
s_tensor,
c_name,
s_name,
style_outdir=save_dir)
else:
print("file exists")
InfoNotifier.InfoNotifier.g_progress_info.append(
get_path.get_style_path() + '已存在，跳过')
except RuntimeError:
print(
'Images are too large to transfer. Size under 1000 are recommended '
+ file_path)
try:
if os.path.exists(style_output) is False:
# save style transfer result
if os.path.exists(
os.path.dirname(style_output)) is False:
os.makedirs(os.path.dirname(style_output))
tar.save(style_output, quality=100)
print(f'result saved into files {style_output}')
InfoNotifier.InfoNotifier.g_progress_info.append(
f'风格图保存到: {style_output}')
else:
# print('exists')
InfoNotifier.InfoNotifier.g_progress_info.append(
style_output + ' 已存在，跳过')
except BaseException as ec:
print(ec)
try:
if e_used is True:
del e
except RuntimeError:
pass