def on_created(self, event):
if event.is_directory:
print('不可向图片文件夹中添加此类文件！ 即将删除！')
time.sleep(5)
help.remove_dir_file(event.src_path)
else:
file_name = event.src_path.split('\\')[-1]
format = file_name.split('.')[-1]
if format != 'JPG':
print('请添加格式为JPG的图片，正在删除错误格式图片！')
time.sleep(5)
os.remove(event.src_path)
else:
data = help.artificial_file_split(event.src_path)
id = data[0]
pic_type = data[1]
pic_size = data[2]
database = help.openDB()
conn = database[0]
cur = database[1]
cur.execute(
"INSERT INTO copy (cultivar_id,pic_type,format,path,pic_size) "
"values (%s,%s,%s,%s,%s)",
(id, pic_type, 'JPG', event.src_path, pic_size))
conn.commit()
cur.close()
conn.close
def pro_process(message):
msg = message.body.decode()
email = json.loads(msg).get('email', None)
pathList = json.loads(msg).get('pathList', None)
# 创建用户目录存放被选中的处理后的图片
dir = help.read_conf(help.getRoot() +
'/config/dataConfig.json')['instrument_compress']
dir = dir + '\\' + email.split('@')[0]
print(dir)
if help.mkdir(dir):
print("创建" + email + "目录成功！")
else:
print("用户目录已存在,清除旧数据")
help.remove_dir_file(dir)
help.mkdir(dir)
database = help.openDB()
conn = database[0]
cur = database[1]
try:
# 对目标图片进行压缩处理并转换为base64存入数据库
for path in pathList:
pic_name = path.split('\\')[-1]
print(pic_name)
image = Image.open(path)
image.thumbnail((600, 400), Image.ANTIALIAS) # 使用抗锯齿模式生成缩略图（压缩图片）
image.save(dir + '\\' + pic_name)
print(pic_name + ' 生成缩略图成功')
with open(dir + '\\' + pic_name, 'rb') as img:
base64_data = base64.b64encode(img.read())
print(str(base64_data, 'utf8'))
base64_data = str(base64_data, 'utf8')
cur.execute(
"update instrument_process_pictures set base64 = %s where path = %s",
(
base64_data,
path,
))
conn.commit()
help.save_redis(
email.split('@')[0] + '_pro_process',
json.dumps({
'status': 'success',
'reason': 'proPic process successfully!'
}))
except:
help.save_redis(
email.split('@')[0] + '_pro_process',
json.dumps({
'status': 'failed',
'reason': 'pic compress failed!'
}))
return True
def save_to_pgs(pathList):
database = help.openDB()
conn = database[0]
cur = database[1]
for path in pathList:
data = help.artificial_file_split(path)
id = data[0]
pic_type = data[1]
pic_size = data[2]
cur.execute(
"INSERT INTO artificial_shot_pictures (cultivar_id,pic_type,format,path,pic_size) "
"values (%s,%s,%s,%s,%s)", (id, pic_type, 'JPG', path, pic_size))
conn.commit()
cur.close()
conn.close
print('执行完毕')
def ProcessPicToPgs(pathList):
# 通过help获取数据库连接对象和操作句柄
database = help.openDB()
conn = database[0]
cur = database[1]
for path in pathList:
# 获取图片文件名
picName = path.split('\\')[-1]
# 使用正则表达式对图片名进行分割
pattern = r'[-|_|.]'
result = re.split(pattern, picName)
angle = result[0]
cultivar_id = result[1]
plant_id = result[2]
# 对日期做出转换
date = str(result[3][:4]) + '-' + str(result[3][4:6]) + '-' + str(
result[3][6:9])
date = datetime.strptime(date, '%Y-%m-%d').date()
revolution_num = result[4]
if len(result) == 9:
process_type = 'LBP'
else:
process_type = 'segmentation'
format = result[-1]
# 获取文件大小
pic_size = os.path.getsize(path)
pic_size = round(pic_size / float(1024 * 1024), 2)
cur.execute(
"INSERT INTO instrument_process_pictures (cultivar_id,plant_id,pic_date,revolution_num, angle, process_type,format, path, pic_size) "
"values (%s,%s,%s,%s,%s,%s,%s,%s,%s)",
(cultivar_id, plant_id, date, revolution_num, angle, process_type,
format, path, pic_size))
conn.commit()
print(picName + '入库成功！')
cur.close()
conn.close()
def OriginPicToPgs(pathList):
database = help.openDB()
conn = database[0]
cur = database[1]
for path in pathList:
# 获取图片的文件名
picName = path.split('\\')[-1]
# 利用正则表达式对文件名进行查分
pattern = r'[-|_|.]'
result = re.split(pattern, picName)
# 获取图片的各种属性准备入库
angle = result[0]
cultivar_id = result[1]
plant_id = result[2]
# 对日期做出转换
date = str(result[3][:4]) + '-' + str(result[3][4:6]) + '-' + str(
result[3][6:9])
date = datetime.strptime(date, '%Y-%m-%d').date()
revolution_num = result[4] # 旋转次数
format = result[-1]
# 获取文件大小
pic_size = os.path.getsize(path)
pic_size = round(pic_size / float(1024 * 1024), 2)
cur.execute(
"INSERT INTO instrument_origin_pictures (cultivar_id,plant_id,format,angle,path,revolution_num,pic_date,pic_size) "
"values (%s,%s,%s,%s,%s,%s,%s,%s)",
(cultivar_id, plant_id, format, angle, path, revolution_num, date,
pic_size))
conn.commit()
print(picName + '入库成功！')
cur.close()
conn.close()
def pack(message):
msg = message.body.decode()
email = json.loads(msg).get('email', None)
ids = json.loads(msg).get('ids', None)
if ids:
database = help.openDB()
conn = database[0]
cur = database[1]
origins = []
for id in ids:
cur.execute(
"select * from instrument_origin_pictures where id = %s",
(id, ))
origin = cur.fetchall()
origins.append(origin[0])
help.save_redis(
email.split('@')[0] + '_pack',
json.dumps({
'status': 'success',
'reason': 'instrument data pack finished!'
}))
return True
def origin_process(message):
msg = message.body.decode()
email = json.loads(msg).get('email', None)
id = json.loads(msg).get('id', None)
database = help.openDB()
conn = database[0]
cur = database[1]
if id:
# 创建用户目录存放被选中的处理后的图片
dir = help.read_conf(help.getRoot() +
'/config/dataConfig.json')['instrument_compress']
dir = dir + '\\' + email.split('@')[0]
print(dir)
if help.mkdir(dir):
print("创建" + email + "目录成功！")
else:
print("用户目录已存在,清除旧数据")
help.remove_dir_file(dir)
help.mkdir(dir)
for i in id:
cur.execute(
"select path from instrument_origin_pictures where id = %s",
(i, ))
result = cur.fetchall()
conn.commit()
if result:
try:
# 读取图片地址
path = result[0][0]
# 获取图片的名称并将图片的格式转换为jpg方便压缩
pic_name = path.split('\\')[-1]
pic_name = pic_name.split('.')[0] + '.jpg'
image = Image.open(path) # 将图片读取出来并
image.thumbnail((600, 400),
Image.ANTIALIAS) # 使用抗锯齿模式生成缩略图（压缩图片）
image.save(dir + '\\' + pic_name)
print(pic_name + ' 生成缩略图成功')
with open(dir + '\\' + pic_name, 'rb') as img:
base64_data = base64.b64encode(img.read())
print(str(base64_data, 'utf8'))
base64_data = str(base64_data, 'utf8')
cur.execute(
"update instrument_origin_pictures set base64 = %s where id = %s",
(
base64_data,
i,
))
conn.commit()
except:
help.save_redis(
'instrument_origin_' + email.split('@')[0],
json.dumps({
'status': 'failed',
'reason': "id为：" + id[i] + "的品种图片处理错误"
}))
help.save_redis(
'instrument_origin_' + email.split('@')[0],
json.dumps({
'status': 'success',
'reason': 'Origin pictures process succeed!'
}))
cur.close()
conn.close()
return True
import base64
import os
import help
database = help.openDB()
conn = database[0]
cur = database[1]
cur.execute(
"select base64 from pic_18510363933_artificial where cultivar_id = 2 and pic_type = '5'"
)
conn.commit()
result = cur.fetchall()
base64str = result[0][0]
print(base64str)
# with open('G:\\mum_pic\\artificial\\processed\\[email protected]\\2\\2太真图-1.JPG', 'rb') as f:
# base64str = base64.b64encode(f.read())
# print(base64str)
# # base64str += '=' * missing_padding
# imgdata = base64.b64decode(base64str)
# file = open("G:\\1.JPG", 'wb')
# file.write(imgdata)
# file.close()
# print(base64str)
# lens = len(base64str)
# lenx = lens - (lens % 4 if lens % 4 else 4)
# missing_padding = 4 - len(base64str) % 4
# if missing_padding:
# base64str += '=' * missing_padding
def pack(email, classification, cultivar_id, qulity):
if classification == 'artificial':
database = help.openDB()
conn = database[0]
cur = database[1]
rootDir = help.read_conf(help.getRoot() +
'/config/dataConfig.json')['user_file']
path = rootDir + '\\' + email.split('@')[0]
nowTime = datetime.now().strftime('%Y-%m-%d_')
# 读取列名
cur.execute(
'select column_name from information_schema.columns where table_schema=%s and table_name=%s',
(
'public',
'artificial_character',
))
headers = cur.fetchall()
header = []
for i in range(len(headers)):
header.append(headers[i][0])
print(header)
try:
# 获取用户需要的指标数据，并转换成dataframe格式
rows = []
path_list = []
for i in cultivar_id:
# 查询特征形状的信息
cur.execute('select * from artificial_character where id = %s',
(i, ))
row = cur.fetchall()
rows.append(row[0])
# 查询指定id 的原图地址
cur.execute(
'select path from artificial_shot_pictures where cultivar_id = %s',
(i, ))
list = cur.fetchall()
path_list.append(list)
print(path_list)
data = pd.DataFrame(rows)
# 创建文件夹
if help.mkdir(path):
print('创建成功目录成功')
else:
print('目录已存在，正在清除旧数据')
help.remove_dir_file(path)
help.mkdir(path)
# 将用户需求的数据写入excel中并保存在指定路径
data.to_excel(path + '\\' + nowTime + '_artificial_characters.xls',
header=header,
index=False)
print('保存excel成功')
for i in range(len(cultivar_id)):
id = cultivar_id[i]
help.mkdir(path + '\\' + id)
for j in range(len(path_list[i])):
shutil.copy(path_list[i][j][0], path + '\\' + id)
print(path_list[i][j][0])
# 将当前用户文件夹中的文件打包为压缩文件
get_file_path = path
set_file_path = path + '\\' + email.split('@')[0] + '.zip'
help.compress(get_file_path, set_file_path)
return set_file_path # 将打包好的地址返回 方便邮件发送
print('打包成功')
except:
print('打包失败')