111

apps/auto_convert3d_new.py

@@ -3,6 +3,7 @@ import os, oss2, time, redis, requests, shutil, sys, subprocess, json, platform
 from PIL import Image, ImageDraw, ImageFont
 from retrying import retry
 import atexit,platform
+import white_purification
 if platform.system() == 'Windows':
     sys.path.append('e:\\libs\\')
 import common
@@ -42,6 +43,8 @@ def down_obj_fromoss(pid,order_id):
     prefix = f'objs/print/{pid}/'
     if ossPath != "":
         prefix = os.path.join("objs","print",pid,ossPath,order_id)
+        if "base/" in ossPath:
+            prefix = os.path.join("objs","print",pid,ossPath)
         prefix = prefix.replace("\\","/")
    
     print(f'prefix:{prefix}')
@@ -109,6 +112,8 @@ def team_check(r):
     if repair_id is None: return
     repair_id = repair_id.decode('utf-8')
 
+    # repair_id = 62922
+
     res = requests.get(f'{getRepairInfo_url}?id={repair_id}')
     print(f'getRepairInfo_url:{getRepairInfo_url}?id={repair_id}')
     print(res.text)
@@ -119,9 +124,16 @@ def team_check(r):
 
     print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()), f'pid：{pid} repair_id:{repair_id} 生成团队审核模型 start model:IndependentRepairTeamcheckGLBQueue', )
     ossPath = down_obj_fromoss(pid,orderId)
-    # if ossPath == "":
-    #     print("ossPath is null")
-    #     return
+    #对文件进行白色提纯处理
+    imagePath = os.path.join(workdir, 'print', pid,pid+"Tex1.jpg")
+    print("开始处理白色提纯")
+    white_purification.white_purification_utils(imagePath)    
+    print("贴图文件白色提纯完成",imagePath)
+    #提纯完重新上传提纯图片
+    ossImagePath = os.path.join("objs/print", pid,ossPath,"texture","process_"+pid+"Tex1.jpg")
+    oss_client.put_object_from_file(f"objs/print/{pid}/{ossPath}/texture/process_{pid}Tex1.jpg",imagePath)
+    print("白色提纯上传图片路径-",ossImagePath,imagePath)
+
     obj_filename = f'{pid}.obj'
     glb_filename = f'{orderId}.glb'
     print('开始转换obj文件为glb文件...')
@@ -141,15 +153,8 @@ def team_check(r):
             config.oss_bucket_3d_view.put_object_from_file(f'{uuid}/3d_view.png', f'D://print/{pid}/{pid}_pic.png')
     
     
-    if ossPath == "model/smsize":
-        ossPath = "smsize"
-    
-    if ossPath == "model/standard_size":
-        ossPath = "normal"
 
-
-    print('上传glb文件到oss...',f'glbs/print/{ossPath}/{glb_filename}',os.path.join(workdir, "print", pid, glb_filename))
-    oss_client.put_object_from_file(f'glbs/print/{ossPath}/{glb_filename}', os.path.join(workdir, "print", pid, glb_filename))
+    oss_client.put_object_from_file(f'glbs/print/order_id/{glb_filename}', os.path.join(workdir, "print", pid, glb_filename))
 
     print(f'{update_repair_status_url}?id={repair_id}')
     res = requests.get(f'{update_repair_status_url}?id={repair_id}')

apps/flat_fridge_glb.py

@@ -20,9 +20,9 @@ def find_blender_bin_path():
         exit(1)
 
 @retry(stop_max_attempt_number=10, wait_fixed=3000)
-def down_obj_fromoss(pid):
+def down_obj_fromoss(pid,orderId):
     print('开始下载obj文件...' , pid)
-    path = os.path.join(workdir, 'print', pid)
+    path = os.path.join(workdir, 'print', pid,orderId)
     if not os.path.exists(path): os.makedirs(path)
     # 根据前缀获取文件列表
     prefix = f'objs/print/{pid}/base/fridge'
@@ -33,17 +33,17 @@ def down_obj_fromoss(pid):
     for file in filelist:
         filename = file.key.split('/')[-1]
         if filename == '': continue
-        if filename.endswith(f'.obj') and find == True:
-            continue
+        # if filename.endswith(f'.obj') and find == True:
+        #     continue
         
-        if filename.endswith(f'{pid}.obj'):
-            find = True
+        # if filename.endswith(f'{pid}.obj'):
+        #     find = True
         localfile = os.path.join(path, filename)
         res = oss_client.get_object_to_file(file.key, localfile)
         print(f'下载文件：{file.key}，状态：{res.status}')
-    if not find:
-        print('找不到obj文件，异常退出')
-        sys.exit(1)
+    # if not find:
+    #     print('找不到obj文件，异常退出')
+    #     sys.exit(1)
     return
 
 
@@ -53,7 +53,7 @@ def down_obj_fromoss(pid):
 
 def team_check(r):
     try:
-        if r.llen('glb:flat_fridge_repair_order') == 0:
+        if r.llen('glb:flat_fridge') == 0:
             time.sleep(5)
             return
     except Exception as e:
@@ -62,19 +62,34 @@ def team_check(r):
         time.sleep(5)
         r = create_redis_connection()
         return
-    pid = r.lpop('glb:flat_fridge_repair_order')
-    if pid is None: return
-    pid = pid.decode('utf-8')
+    repair_id = r.lpop('glb:flat_fridge')
+    if repair_id is None: return
+    repair_id = repair_id.decode('utf-8')
+
+    res = requests.get(f'{getRepairInfo_url}?id={repair_id}')
+    print(f'getRepairInfo_url:{getRepairInfo_url}?id={repair_id}')
+    print(res.text)
+    pid = res.json()['data']['pid']
+    orderId = res.json()['data']['order_id']
+    pid = str(pid)
+    orderId = str(orderId)
+
     #下载数据
-    down_obj_fromoss(pid)
+    down_obj_fromoss(pid,orderId)
     
     obj_filename = f'{pid}.obj'
-    glb_filename = f'{pid}.glb'
+    glb_filename = f'{orderId}.glb'
     print('开始转换obj文件为glb文件...')
-    os.system(f'gltfpack -c -i {os.path.join(workdir, "print", pid, obj_filename)} -o {os.path.join(workdir, "print", pid, glb_filename)} -vt 16 -vc 16')
+    os.system(f'gltfpack -c -i {os.path.join(workdir, "print", pid,orderId, obj_filename)} -o {os.path.join(workdir, "print", pid,orderId, glb_filename)} -vt 16 -vc 16')
     #上传glb文件到oss
-    oss_client.put_object_from_file(f'glbs/print/flat_fridge/{glb_filename}', os.path.join(workdir, "print", pid, glb_filename))
-    shutil.rmtree(os.path.join(workdir, 'print', pid), ignore_errors=True)
+    oss_client.put_object_from_file(f'glbs/print/flat_fridge/order_id/{glb_filename}', os.path.join(workdir, "print", pid,orderId, glb_filename))
+    print(f'{update_repair_status_url}?id={repair_id}')
+    res = requests.get(f'{update_repair_status_url}?id={repair_id}')
+    print('更新团队审核状态:', res.text)
+    # shutil.rmtree(os.path.join(workdir, 'print', pid), ignore_errors=True)
+    print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()), f'pid：{pid} 生成团队审核模型 end')
+
+    # shutil.rmtree(os.path.join(workdir, 'print', pid), ignore_errors=True)
     print(time.strftime('%Y-%m-%d %H:%M:%S', time.localtime()), f'pid：{pid} 压平冰箱贴的glb已生成 end')
 
 def create_redis_connection():
@@ -109,6 +124,8 @@ if __name__ == '__main__':
     Endpoint = 'oss-cn-shanghai.aliyuncs.com'
     Bucket = 'suwa3d-securedata'
     oss_client = oss2.Bucket(oss2.Auth(AccessKeyId, AccessKeySecret), Endpoint, Bucket)
+    getRepairInfo_url = 'https://repair.api.suwa3d.com/api/modelRepairOrder/teamCheckGLBInfo'
+    update_repair_status_url = 'https://repair.api.suwa3d.com/api/modelRepairOrder/updateStatusToWaitingTeamCheckingStatus'
     if platform.system() == 'Windows':
         workdir = 'D:\\'
     else:

apps/white_purification.py

@@ -0,0 +1,138 @@
+import argparse
+import cv2
+import numpy as np
+
+def find_last_x(image, slope_threshold = 1000):
+    x,y = [],[]
+    hist, bins = np.histogram(image, bins=256, range=[0, 256])
+
+    #找到50以内的最高峰
+    max_y , max_i = 0, 5
+    for i in range(5, 25):
+        if hist[i] > max_y:
+            max_y = hist[i]
+            max_i = i
+    print(f'50以内最高峰值y：{max_y}，最高峰位置x：{max_i}')
+
+    for i in range(2, max_i):
+        x.append(i)
+        y.append(hist[i])
+    slopes = [abs(y[i + 1] - y[i]) for i in range(len(x) - 1)]
+
+    current_interval = []
+    max_interval = []
+    max_x = {}
+    for i, slope in enumerate(slopes):
+        current_interval.append(slope)
+        if slope >= slope_threshold:
+            if len(current_interval) > len(max_interval):
+                max_interval = current_interval.copy()
+                max_x[x[i]] = slope
+            current_interval = []
+
+    print(max_x)
+    last_x = list(max_x)[-1]
+    last_y = max_x[last_x]
+    return last_x, last_y
+
+
+def find_last_high(image, slope_threshold = 2500):
+    x = []
+    y = []
+    hist, bins = np.histogram(image, bins=255, range=[2, 255])
+
+    #找到200以上的最高峰
+    max_y = 0
+    max_i = 254
+    for i in range(220, 255):
+        if hist[i] > max_y:
+            max_y = hist[i]
+            max_i = i
+    print(f'200以上的最高峰值y：{max_y}，最高峰位置x：{max_i}')
+
+    for i in range(max_i, 255):
+        x.append(i)
+        y.append(hist[i])
+    slopes = [abs(y[i + 1] - y[i]) for i in range(len(x) - 1)]
+
+    current_interval = []
+    max_interval = []
+    max_x = {}
+    find = False
+    for i in range(len(slopes) - 1, -1, -1):
+        slope = slopes[i]
+        current_interval.append(slope)
+        if slope >= slope_threshold:
+            find = True
+            if len(current_interval) > len(max_interval):
+                max_interval = current_interval.copy()
+                max_x[x[i]] = slope
+            current_interval = []
+        #如果没有找到200以上很平，而且高度小于5000，就按220位置削平
+        if not find and hist[220] < 5000:
+            max_x[220] = hist[220]
+
+    print(max_x)
+    if len(max_x) > 0:
+        last_x = list(max_x)[0]
+        last_y = max_x[last_x]
+    else:
+        print(f'找不到200以上曲线较平的区间，使用254作为最高峰')
+        last_x = 254
+        last_y = hist[254]
+    return last_x, last_y
+
+
+def ps_color_scale_adjustment(image, shadow=0, highlight=255, midtones=1):
+    '''
+    模拟 PS 的色阶调整； 0 <= Shadow < Highlight <= 255
+    :param image: 传入的图片
+    :param shadow: 黑场(0-Highlight)
+    :param highlight: 白场(Shadow-255)
+    :param midtones: 灰场(9.99-0.01)
+    :return: 图片
+    '''
+    if highlight > 255:
+        highlight = 255
+    if shadow < 0:
+        shadow = 0
+    if shadow >= highlight:
+        shadow = highlight - 2
+    if midtones > 9.99:
+        midtones = 9.99
+    if midtones < 0.01:
+        midtones = 0.01
+    image = np.array(image, dtype=np.float16)
+    # 计算白场 黑场离差
+    Diff = highlight - shadow
+    image = image - shadow
+    image[image < 0] = 0
+    image = (image / Diff) ** (1 / midtones) * 255
+    image[image > 255] = 255
+    image = np.array(image, dtype=np.uint8)
+
+    return image
+
+
+def white_purification_utils(image_path):
+    input_image = cv2.imread(image_path)
+    # low_x_thresh, low_y_frequency = low_find_histogram_range(input_image, low_y_limit)
+    low_x_thresh, low_y_frequency = find_last_x(input_image)
+    # high_x_thresh, high_y_frequency = high_find_histogram_range(input_image, high_y_limit)
+    high_x_thresh, high_y_frequency = find_last_high(input_image)
+    print(f"{low_x_thresh} 区间, {low_y_frequency} 频次")
+    print(f"{high_x_thresh} 区间, {high_y_frequency} 频次")
+    high_output_image = ps_color_scale_adjustment(input_image, shadow=low_x_thresh, highlight=high_x_thresh, midtones=1)
+    file_extension = image_path.lower().split('.')[-1]
+    if file_extension == 'png':
+        cv2.imwrite(image_path, high_output_image)  # PNG格式无需压缩参数
+    else:
+        # cv2.imwrite(image_path.replace(".jpg", '_white.jpg'), high_output_image, [cv2.IMWRITE_JPEG_QUALITY, 95])  # 保存图片的质量是原图的 95%
+        cv2.imwrite(image_path, high_output_image, [cv2.IMWRITE_JPEG_QUALITY, 95])  # 保存图片的质量是原图的 95%
+
+
+# if __name__ == "__main__":
+#     parser = argparse.ArgumentParser()
+#     parser.add_argument("-i","--image_path", type=str, default="")
+#     args = parser.parse_args()
+#     white_purification_utils(args.image_path)