257 lines
9.2 KiB
Python
257 lines
9.2 KiB
Python
import os
|
||
import math
|
||
from PIL import Image
|
||
from concurrent.futures import ThreadPoolExecutor
|
||
|
||
def resize_and_reduce_quality(image_path, output_path, target_width = None):
|
||
try:
|
||
# 检查图片文件大小
|
||
if os.path.getsize(image_path) < 10 * 1024 * 1024: # 10MB
|
||
print("图片文件大小小于10MB，不进行调整")
|
||
return image_path
|
||
|
||
|
||
# 打开图片
|
||
with Image.open(image_path) as img:
|
||
# 计算新的高度以保持宽高比
|
||
if target_width is None:
|
||
target_width = img.width
|
||
aspect_ratio = img.height / img.width
|
||
new_height = int(target_width * aspect_ratio)
|
||
|
||
# 调整图片大小
|
||
img_resized = img.resize((target_width, new_height), Image.LANCZOS)
|
||
|
||
# 降低图片质量
|
||
quality = 70 # 质量从1（最差）到95（最好），可以根据需要调整
|
||
img_resized.save(output_path, quality=quality)
|
||
|
||
return output_path
|
||
except Exception as e:
|
||
return f"调整图片大小和质量时出现问题: {str(e)}"
|
||
|
||
def get_picture_nums(source_path: str) -> int:
|
||
picture_count = 0
|
||
for root, dirs, files in os.walk(source_path):
|
||
for file in files:
|
||
if file.lower().endswith(('.jpg', '.jpeg', '.png')) and not file.startswith('merged_thumbnail'):
|
||
picture_count += 1
|
||
return picture_count
|
||
|
||
def collect_defect_data(
|
||
Y: str,
|
||
picture_dir: str,
|
||
search_file_list: list = [],
|
||
) -> tuple[int, dict]:
|
||
"""
|
||
收集指定年份的缺陷图片数据，并根据布尔值决定是否扫描特定类型的缺陷图。
|
||
|
||
Args:
|
||
Y: 叶片号，如 "Y1"、"Y2"、"Y3"
|
||
picture_dir: 图片根目录
|
||
search_file_list (list, optional): 要搜索的文件列表.规定为3个元素
|
||
|
||
Returns:
|
||
(缺陷图片总数, 缺陷图片文件名字典)
|
||
"""
|
||
|
||
total_num = 0
|
||
result_dict = {}
|
||
|
||
try:
|
||
for defect_type in search_file_list:
|
||
dir_path = os.path.join(picture_dir, Y, defect_type)
|
||
num, img_dict = get_picture_nums_and_image_with_name(dir_path)
|
||
total_num += num
|
||
result_dict.update(img_dict)
|
||
except Exception as e:
|
||
print(f"获取图片数据时出现问题: {str(e)},搜寻的目录：{dir_path}")
|
||
|
||
return total_num, result_dict
|
||
|
||
def get_picture_nums_and_image_with_name(source_path: str) -> tuple[int, dict]:
|
||
"""
|
||
获取指定目录下图片的数量，并返回每个图片的路径和名称（字典）
|
||
|
||
Args:
|
||
source_path (str): 要搜索的目录路径
|
||
|
||
Returns:
|
||
tuple: 包含两个元素的元组
|
||
picture_count (int): 图片数量
|
||
image_with_name (dict): 图片路径和名称的字典，格式为 {图片名称: 图片完整路径}
|
||
"""
|
||
picture_count = 0
|
||
image_with_name = {}
|
||
name_list = []
|
||
|
||
for root, dirs, files in os.walk(source_path):
|
||
for file in files:
|
||
if file.lower().endswith(('.jpg', '.jpeg', '.png')) and not file.startswith('merged_thumbnail'):
|
||
picture_count += 1
|
||
image_with_name[os.path.splitext(file)[0]] = os.path.join(root, file)
|
||
|
||
return picture_count, image_with_name
|
||
|
||
|
||
def find_image(directory, image_name):
|
||
"""
|
||
在指定目录中查找指定名称的图片文件
|
||
|
||
参数:
|
||
directory (str): 要搜索的目录路径
|
||
image_name (str): 要查找的图片文件名(可带扩展名或不带)
|
||
|
||
返回:
|
||
str: 找到的图片完整路径，如果未找到则返回None
|
||
"""
|
||
# 支持的图片扩展名列表
|
||
image_extensions = ['.jpg', '.jpeg', '.png', '.gif', '.bmp', '.tiff', '.webp']
|
||
|
||
# 遍历目录中的所有文件
|
||
for root, dirs, files in os.walk(directory):
|
||
for file in files:
|
||
# 获取文件名和扩展名
|
||
filename, ext = os.path.splitext(file)
|
||
|
||
# 检查是否匹配图片名称(带或不带扩展名)
|
||
if (file.lower() == image_name.lower() or
|
||
filename.lower() == image_name.lower() and ext.lower() in image_extensions):
|
||
return os.path.join(root, file)
|
||
|
||
return None
|
||
|
||
async def make_Thumbnail(source_path: str, output_path: str, size: tuple = (436, 233)) -> str:
|
||
"""获取目录下所有图片，将所有图片合并制作略缩图并保存
|
||
|
||
Args:
|
||
source_path: 源目录
|
||
output_path: 输出目录
|
||
size: 合并后的略缩图总大小 (宽度, 高度)
|
||
"""
|
||
print("略缩图处理中")
|
||
|
||
try:
|
||
if not os.path.exists(output_path):
|
||
print(f"无输出目录，创建中，输出目录为：{output_path}")
|
||
os.makedirs(output_path)
|
||
except Exception as e:
|
||
print(f"输出目录有问题：{e}")
|
||
return ""
|
||
#如果存在merged_thumbnail.jpg文件，则直接返回该文件路径
|
||
if os.path.exists(os.path.join(output_path,'merged_thumbnail.jpg')):
|
||
print(f"已有略缩图，不用处理, 目前如需重新生成，请去往{output_path}目录 删除 merged_thumbnail.jpg 图片")
|
||
"""
|
||
此处可预留接口，询问用户是否重新生成一份略缩图
|
||
"""
|
||
|
||
return os.path.join(output_path,'merged_thumbnail.jpg')
|
||
print("目录中无略缩图，合并略缩图中")
|
||
# 获取源目录下所有的图片文件
|
||
try:
|
||
image_files = []
|
||
for root, dirs, files in os.walk(source_path):
|
||
for file in files:
|
||
if file.lower().endswith(('.jpg', '.jpeg', '.png')):
|
||
image_files.append(os.path.join(root, file))
|
||
except Exception as e:
|
||
print(f"递归获取图片失败,原因：{e}")
|
||
|
||
if not image_files:
|
||
print("源目录中没有找到图片文件")
|
||
return ""
|
||
|
||
# 计算每个缩略图的大小
|
||
num_images = len(image_files)
|
||
target_width, target_height = size
|
||
|
||
# 计算最佳的缩略图排列方式
|
||
# 先尝试计算每行可以放多少个缩略图
|
||
aspect_ratio = target_width / target_height
|
||
cols = math.ceil(math.sqrt(num_images * aspect_ratio))
|
||
rows = math.ceil(num_images / cols)
|
||
|
||
# 计算单个缩略图的大小
|
||
thumb_width = target_width // cols
|
||
thumb_height = target_height // rows
|
||
|
||
# 创建线程池处理图片
|
||
with ThreadPoolExecutor() as executor:
|
||
thumbnails = list(executor.map(
|
||
lambda file: create_thumbnail(file, (thumb_width, thumb_height)),
|
||
image_files
|
||
))
|
||
|
||
# 过滤掉 None 值
|
||
thumbnails = [thumb for thumb in thumbnails if thumb is not None]
|
||
|
||
if not thumbnails:
|
||
print("没有成功创建任何略缩图")
|
||
return ""
|
||
|
||
# 计算实际需要的行数和列数
|
||
actual_cols = min(len(thumbnails), cols)
|
||
actual_rows = math.ceil(len(thumbnails) / actual_cols)
|
||
|
||
# 创建合并后的图像
|
||
merged_image = Image.new('RGB', (actual_cols * thumb_width, actual_rows * thumb_height))
|
||
|
||
# 粘贴缩略图
|
||
for index, thumb in enumerate(thumbnails):
|
||
row = index // actual_cols
|
||
col = index % actual_cols
|
||
merged_image.paste(thumb, (col * thumb_width, row * thumb_height))
|
||
|
||
# 如果最终尺寸不完全匹配，调整大小
|
||
if merged_image.size != size:
|
||
merged_image = merged_image.resize(size, Image.LANCZOS)
|
||
|
||
# 保存合并后的略缩图
|
||
merged_thumbnail_path = os.path.join(output_path, 'merged_thumbnail.jpg')
|
||
merged_image.save(merged_thumbnail_path)
|
||
|
||
print(f"合并后的略缩图已保存到：{merged_thumbnail_path}")
|
||
return merged_thumbnail_path
|
||
|
||
def create_thumbnail(file_path: str, size: tuple) -> Image:
|
||
"""创建单个图片的略缩图
|
||
|
||
Args:
|
||
file_path: 图片文件路径
|
||
size: 缩略图大小
|
||
"""
|
||
try:
|
||
with Image.open(file_path) as img:
|
||
# 保持原始宽高比
|
||
img.thumbnail(size, Image.LANCZOS)
|
||
|
||
# 创建新图像确保尺寸一致
|
||
new_img = Image.new('RGB', size)
|
||
new_img.paste(img, ((size[0] - img.width) // 2, (size[1] - img.height) // 2))
|
||
return new_img
|
||
except Exception as e:
|
||
print(f"图片处理有问题：{e}")
|
||
return None
|
||
|
||
def process_picture_data(picture_data : list[dict],
|
||
image_source_to_find : list[str],
|
||
quexian_type : str,
|
||
dianxing_type : str) -> tuple[list[str], list[str]]:
|
||
"""处理从数据库获取的图片数据
|
||
|
||
Args:
|
||
picture_data (list[dict]): 图片数据
|
||
image_source_to_find (list[str]): 要查找的图片来源枚举(外内防雷)
|
||
quexian_type (str): 缺陷类型枚举值
|
||
dianxing_type (str): 典型类型枚举值
|
||
Returns:
|
||
tuple(
|
||
defct_pictures, 缺陷图列表
|
||
dianxing_pictures 典型图列表
|
||
)
|
||
"""
|
||
#过滤目标来源的图片数据
|
||
picture_data = [pic for pic in picture_data if pic['imageSource'] in image_source_to_find]
|
||
#分别择出缺陷图和典型图
|
||
return [pic for pic in picture_data if pic['imageType'] == quexian_type], [pic for pic in picture_data if pic['imageType'] == dianxing_type]
|
||
|