程序优化
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dongchangxi committed
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@@ -1,5 +1,8 @@
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import redis,sys,os,re,oss2,shutil,time
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import redis,sys,os,re,oss2,shutil,time,cv2
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import json
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import requests
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import platform
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import numpy as np
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import xml.etree.ElementTree as ET
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from PIL import ImageGrab
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if platform.system() == 'Windows':
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@@ -222,14 +225,14 @@ def uploadControlPointsOss(pid):
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#截屏保存
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def saveScreenImg(pid):
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#获取当前的日志
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if not os.path.exists(os.path.join(config.workdir,"screen", time.strftime("%y%m%d" time.localtime()))):
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os.makedirs(os.path.join(config.workdir,"screen", time.strftime("%y%m%d" time.localtime())))
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if not os.path.exists(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime()))):
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os.makedirs(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime())))
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screenshot = ImageGrab .grab()
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screenshot.save(os.path.join(config.workdir,"screen", time.strftime("%y%m%d" time.localtime())),str(pid)+".png")
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screenshot.save(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime()))+"/"+str(pid)+".png")
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#移动到e盘
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if not os.path.exists(os.path.join(config.sharedir,"screen", time.strftime("%y%m%d" time.localtime()))):
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os.makedirs(os.path.join(config.sharedir,"screen", time.strftime("%y%m%d" time.localtime())))
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shutil.copytree(os.path.join(config.workdir,"screen", time.strftime("%y%m%d" time.localtime())), os.path.join(config.sharedir,"screen", time.strftime("%y%m%d" time.localtime())))
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if not os.path.exists(os.path.join(config.sharedir,"screen", time.strftime("%y%m%d",time.localtime()))):
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os.makedirs(os.path.join(config.sharedir,"screen", time.strftime("%y%m%d",time.localtime())))
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shutil.copy(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime()))+"\\"+str(pid)+".png", os.path.join(config.sharedir,"screen", time.strftime("%y%m%d",time.localtime())))
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#文件夹的移动和删除
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@@ -247,4 +250,156 @@ def removeFolder(pid):
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file_time = os.path.getmtime(os.path.join(config.workdir, 'finished', file))
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now_time = time.time()
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if (now_time - file_time) > 259200:
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shutil.rmtree(os.path.join(config.workdir, 'finished', file), ignore_errors=True)
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shutil.rmtree(os.path.join(config.workdir, 'finished', file), ignore_errors=True)
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def find_last_x(image, slope_threshold = 1000):
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x = []
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y = []
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hist, bins = np.histogram(image, bins=256, range=[0, 256])
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#找到50以内的最高峰
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max_y = 0
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max_i = 5
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for i in range(5, 50):
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if hist[i] > max_y:
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max_y = hist[i]
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max_i = i
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print(f'50以内最高峰值y：{max_y}，最高峰位置x：{max_i}')
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for i in range(2, max_i):
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x.append(i)
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y.append(hist[i])
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slopes = [abs(y[i + 1] - y[i]) for i in range(len(x) - 1)]
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current_interval = []
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max_interval = []
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max_x = {}
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for i, slope in enumerate(slopes):
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current_interval.append(slope)
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if slope >= slope_threshold:
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if len(current_interval) > len(max_interval):
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max_interval = current_interval.copy()
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max_x[x[i]] = slope
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current_interval = []
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print(max_x)
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last_x = list(max_x)[-1]
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last_y = max_x[last_x]
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return last_x, last_y
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def high_find_histogram_range(image, target_frequency):
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'''
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循环查找在 target_frequency (y)频次限制下的直方图区间值(x)
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:param image: 导入图片
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:param target_frequency: 直方图 y 频次限制条件
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:return: 直方图区间 x，和 该区间频次 y
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'''
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# 计算灰度直方图
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hist, bins = np.histogram(image, bins=256, range=[0, 256])
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# 初始化区间和频次
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interval = 255
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frequency = hist[255]
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while frequency < target_frequency:
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# 更新区间和频次
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interval -= 1
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# 检查直方图的频次是否为None，如果频次是None，则将其设为0，这样可以避免将None和int进行比较报错。
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frequency = hist[interval] if hist[interval] is not None else 0
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frequency += hist[interval] if hist[interval] is not None else 0
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# 如果频次接近10000则停止循环
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if target_frequency - 2000 <= frequency <= target_frequency + 2000:
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break
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return interval, frequency
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def ps_color_scale_adjustment(image, shadow=0, highlight=255, midtones=1):
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'''
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模拟 PS 的色阶调整； 0 <= Shadow < Highlight <= 255
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:param image: 传入的图片
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:param shadow: 黑场(0-Highlight)
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:param highlight: 白场(Shadow-255)
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:param midtones: 灰场(9.99-0.01)
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:return: 图片
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'''
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if highlight > 255:
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highlight = 255
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if shadow < 0:
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shadow = 0
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if shadow >= highlight:
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shadow = highlight - 2
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if midtones > 9.99:
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midtones = 9.99
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if midtones < 0.01:
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midtones = 0.01
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image = np.array(image, dtype=np.float16)
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# 计算白场 黑场离差
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Diff = highlight - shadow
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image = image - shadow
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image[image < 0] = 0
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image = (image / Diff) ** (1 / midtones) * 255
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image[image > 255] = 255
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image = np.array(image, dtype=np.uint8)
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return image
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def remove_gray_and_sharpening(jpg_path):
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#low_y_limit = 25000
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high_y_limit = 13000
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input_image = cv2.imread(jpg_path)
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# low_x_thresh, low_y_frequency = low_find_histogram_range(input_image, low_y_limit)
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low_x_thresh, low_y_frequency = find_last_x(input_image, 1000)
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high_x_thresh, high_y_frequency = high_find_histogram_range(input_image, high_y_limit)
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print(f"{low_x_thresh} 区间, {low_y_frequency} 频次")
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print(f"{high_x_thresh} 区间, {high_y_frequency} 频次")
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high_output_image = ps_color_scale_adjustment(input_image, shadow=low_x_thresh, highlight=high_x_thresh, midtones=1)
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cv2.imwrite(jpg_path, high_output_image, [cv2.IMWRITE_JPEG_QUALITY, 95]) # 保存图片的质量是原图的 95%
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#读取指定路径判断是否对齐成功
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def isAlignNums(strPid):
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#拼接路径
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csvPath = os.path.join(config.workdir, strPid, strPid+"_align.csv")
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print(csvPath)
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#判断文件是否存在
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if os.path.exists(csvPath) == False:
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return "rebuild"
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#读取文件行数
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lines = ""
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with open(csvPath, 'r') as f:
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lines = f.readlines()
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#获取长度
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lines = len(lines) - 1
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#获取pid对应的 photo1 和 photo2 的数量
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photo1Num = 0
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photo2Num = 0
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for file in os.listdir(os.path.join(config.workdir, strPid, 'photo1')):
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if file.endswith('.jpg'):
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photo1Num += 1
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for file in os.listdir(os.path.join(config.workdir, strPid, 'photo2')):
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if file.endswith('.jpg'):
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photo2Num += 1
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#获取图片总数
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totalPhotos = photo1Num + photo2Num
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#比对对齐数量
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if totalPhotos - lines >= 4:
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return "rebuild"
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return True
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#消息通知
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def notify(content):
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if content == "":
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return "content 不能为空"
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for user_agent_id in config.notify_user_Ids:
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data = {
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'userId': user_agent_id,
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'message': content,
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}
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headers = {'Content-Type': 'application/json'}
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message_send_url = "https://mp.api.suwa3d.com/api/qyNotify/sendMessage?userId="+user_agent_id+"&message="+content
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response = requests.post(message_send_url, data=json.dumps(data), headers=headers)
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