def convert_freemarker_path(fm_path):
"""
把指定目录下的模版文件中的Freemark语法，同一替换成Jinjia2语法
:param fm_path: 指定目录
:return:无
"""
path_list = filecm.search_files(fm_path, ".tpl,.json,.ftl")
for tpl_path in path_list:
fm_str = filecm.read_str(file_name=tpl_path)
jj_str = freemarker_to_jinjia2(fm_str)
diffcm.diff_by_text(fm_str, jj_str)
filecm.save_str(jj_str, file_name=tpl_path)
def scale_img_folder(folder_path, scale_width, scale_height, ext=".png,.jpg,jpeg", match=None):
"""
缩放指定图片文件目录下所有图片到指定大小并覆盖原图
@:param folder_path 指定图片目录
@:param scale_width 宽度
@:param scale_height 高度
@return: 无
"""
# 对图片目录遍历
path_list = filecm.search_files(folder_path, ext=ext, match=match)
# 对所有文件进行缩放
for file_path in path_list:
scale_img_file(file_path, scale_width, scale_height)
def make_by_path(self, path, path_map, cfg_obj):
"""
按照指定模版目录,和路径Map,进行代码生成
:param path: 模版目录
:param path_map: 路径Map
:param cfg_obj: 配置数据
:return: 文件生成数
"""
make_count = 0
path = os.path.join(self.tpl_path, path)
tpl_list = filecm.search_files(path, ".tpl")
for tpl_path in tpl_list:
out_file_tpl = path_map[filecm.short_name(tpl_path)]
self.make_by_tpl(tpl_path, out_file_tpl, cfg_obj)
make_count += 1
return make_count
def LoadTexture(self):
# 提前准备好的6个图片
# imgFiles = [str(i) + '.jpg' for i in range(1, 7)]
# 取得图片列表
imgFiles = filecm.search_files(cfg["img_root"], cfg['img_ext'],
r'^[^\.]+')
for i in range(6):
img = Image.open(imgFiles[i])
width, height = img.size
img = img.tobytes('raw', 'RGBX', 0, -1)
# 根据纹理参数返回n个纹理索引。
glGenTextures(2)
glBindTexture(GL_TEXTURE_2D, i)
glTexImage2D(GL_TEXTURE_2D, 0, 4, width, height, 0, GL_RGBA,
GL_UNSIGNED_BYTE, img)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_CLAMP)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_CLAMP)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST)
glTexParameterf(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST)
glTexEnvf(GL_TEXTURE_ENV, GL_TEXTURE_ENV_MODE, GL_DECAL)
default_config = """
{
"img_root": "./images/faces/",
"max_count" : 10,
"fps": 1,
"save_path": "./temp/output.pptx",
"width": 1024,
"height": 683
}
"""
# 加载配置文件
cfg = loadcfgcm.load("file_pptx_from_img.json", default_config)
pptFile = pptx.Presentation()
# 取得图片列表
path_list = filecm.search_files(cfg["img_root"], '.jpeg', r'^[^\.]+')
# 按图片编号顺序导入
for fn in path_list:
slide = pptFile.slides.add_slide(pptFile.slide_layouts[1])
# 为PPTX文件当前幻灯片中第一个文本框设置文字，本文代码中可忽略
slide.shapes.placeholders[0].text = fn[:fn.rindex('.')]
# 导入并为当前幻灯片添加图片，起始位置和尺寸可修改
slide.shapes.add_picture(fn, Inches(0), Inches(0), Inches(10), Inches(7.5))
pptFile.save('./temp/img_to_pptx.pptx')
"action" : "copy|move",
"src_path": "",
"target_path": "",
"target_w": 1280,
"target_h": 800,
"src_ext": "png",
"target_ext": "jpg"
}
"""
# 加载配置文件
cfg = loadcfgcm.load("file_img_convert.json", default_config)
# 检索图片列表
search_path = ''
path_list = filecm.search_files(cfg["src_path"], '.' + cfg["src_ext"],
r'^[^\.]+')
logcm.print_obj(path_list, 'path_list')
# 横版图片路径列表
w_list = []
h_list = []
count = 1
for path in path_list:
# 调整图片尺寸并保存
(file_path, file_name) = os.path.split(path)
(short_name, extension) = os.path.splitext(file_name)
# 修改大小
im_new = imagecm.resize(path,
cfg["target_w"],
cfg["target_h"],
keep_ratio=True)
"title_line": 0,
"col_titles": ["基金名称", "投资者名称", "客户类型", "证件类型", "证件号码", "????"]
}],
"YYYYYY": [{
"sheet_name": "客户明细J",
"title_line": 0,
"col_titles": ["????", "客户名称", "客户类型", "证件类型", "证件号码", "持有份额"]
}]
}
"""
# 加载配置文件
config_map = loadcfgcm.load("file_load_xls.json", default_config)
# 取得指定目录下的文件列表
path_list = filecm.search_files(root_dir, '.xlsx,.xls', r'^[^~]+')
logcm.print_obj(path_list, "path_list")
# 读取文件数
read_file_cnt = 0
# 读取数据行数
read_line_cnt = 0
# 路径列表
for path in path_list:
# 短文件名
short_name = filecm.short_name(path)
# 根据文件名取得配置列表
if short_name not in config_map:
print("==========未找到配置：%s" % short_name)
continue
{
"remark" : "图片按照横竖分类复制或移动",
"action" : "copy|move",
"src_path": "",
"target_path_w": "",
"target_path_h": "",
"skeep_exist": true
}
"""
# 加载配置文件
cfg = loadcfgcm.load("file_img_movecopy.json", default_config)
# 检索图片列表
search_path = ''
path_list = filecm.search_files(cfg["src_path"], '.jpg', r'^[^\.]+')
logcm.print_obj(path_list, 'path_list')
# 横版图片路径列表
w_list = []
h_list = []
for path in path_list:
if imagecm.is_landscape(path):
w_list.append(path)
else:
h_list.append(path)
logcm.print_obj(w_list, 'w_list')
logcm.print_obj(h_list, 'h_list')
# 复制图片
if cfg['action'] == "copy":
# 加载配置文件
cfg = loadcfgcm.load("cv_video_from_img.json", default_config)
# 创建目录
filecm.makedir(cfg['save_path'], True)
filecm.makedir('./temp/cv/video-from-img')
# 新建视频写入类
fourcc = cv2.VideoWriter_fourcc(*"MJPG")
videoWriter = cv2.VideoWriter(cfg['save_path'], fourcc, cfg['fps'],
(cfg['width'], cfg['height']))
im_output = VideoImageOutput(videoWriter)
# 取得图片列表
path_list = filecm.search_files(cfg["img_root"], cfg['img_ext'], r'^[^\.]+')
# 取得处理数量
max_size = cfg['max_count']
if max_size > len(path_list):
max_size = len(path_list)
# 减速列表
slow_move_h = imagecm.slow_down(-1 * cfg['width'], 0, 10)
slow_move_v = imagecm.slow_down(-1 * cfg['height'], 0, 10)
# 加速列表
speed_move_h = imagecm.speed_up(0, cfg['width'], 10)
speed_move_v = imagecm.speed_up(0, cfg['height'], 10)
# 压缩
speed_zip = imagecm.speed_up(0.01, 1.0, 10)
slow_zip = imagecm.slow_down(1.0, 0.01, 10)
# 放大
"""
from common import filecm
from common import imagecm
from common import logcm
# 读取图片尺寸
img_path = './images/draw_box_result.jpg'
size = imagecm.get_size(img_path)
logcm.print_obj(size, 'size')
# 调整图片尺寸并保存
save_path = './temp/draw_box_result_thumb.jpg'
imagecm.resize(img_path, 500, 500, save_path, keep_ratio=True)
# 检索图片列表
search_path = '/Volumes/Transcend/data/down/aaa/photo/makeH'
path_list = filecm.search_files(search_path, '.jpg', r'^[^\.]+')
logcm.print_obj(path_list, 'path_list')
# 横版图片路径列表
copy_list = []
for path in path_list:
if imagecm.is_landscape(path):
copy_list.append(path)
logcm.print_obj(copy_list, 'copy_list')
# 复制图片
copy_path = '/Volumes/Transcend/data/down/aaa/photo/makeW'
filecm.move_files(copy_list, copy_path)