feat 新增接口描述 docs页面 ，新增S3 图片get upload 操作，整理代码

fix

app/service/design/items/bag.py

@@ -1,6 +1,7 @@
+import random
+
 from .builder import ITEMS
 from .clothing import Clothing
-import random
 
 
 @ITEMS.register_module()

app/service/design/items/body.py

@@ -1,4 +1,5 @@
 import cv2
+
 from .builder import ITEMS
 from .pipelines import Compose
 

app/service/design/items/pipelines/contour_detection.py

@@ -1,9 +1,8 @@
-import logging
-
-from ..builder import PIPELINES
 import cv2
 import numpy as np
 
+from ..builder import PIPELINES
+
 
 @PIPELINES.register_module()
 class ContourDetection(object):
@@ -11,7 +10,7 @@ class ContourDetection(object):
         # logging.info("ContourDetection run ")
         pass
 
-    #@ RunTime
+    # @ RunTime
     def __call__(self, result):
         # shoe diff
         if result['name'] == 'shoes':

app/service/design/items/pipelines/loading.py

@@ -1,12 +1,5 @@
-import io
-import logging
-
 import cv2
-import numpy as np
-from PIL import Image
-from minio import Minio
 
-from app.core.config import *
 from app.service.utils.oss_client import oss_get_image
 from ..builder import PIPELINES
 
@@ -17,11 +10,7 @@ class LoadImageFromFile(object):
         self.path = path
         self.color = color
         self.print_dict = print_dict
-        self.minio_client = Minio(
+        # self.minio_client = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
-            f"{MINIO_URL}",
-            access_key=MINIO_ACCESS,
-            secret_key=MINIO_SECRET,
-            secure=MINIO_SECURE)
 
     def __call__(self, result):
         result['image'], result['pre_mask'] = self.read_image(self.path)
@@ -53,11 +42,13 @@ class LoadImageFromFile(object):
                            f"bag, shoes, hairstyle, earring.")
         return keypoint
 
-    def read_image(self, image_path):
+    @staticmethod
+    def read_image(image_path):
         image_mask = None
-        file = self.minio_client.get_object(image_path.split("/", 1)[0], image_path.split("/", 1)[1]).data
+        # file = self.minio_client.get_object(image_path.split("/", 1)[0], image_path.split("/", 1)[1]).data
-        image = cv2.imdecode(np.frombuffer(file, np.uint8), 1)
+        # image = cv2.imdecode(np.frombuffer(file, np.uint8), 1)
 
+        image = oss_get_image(bucket=image_path.split("/", 1)[0], object_name=image_path.split("/", 1)[1], data_type="cv2")
         if len(image.shape) == 2:
             image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
         if image.shape[2] == 4:  # 如果是四通道 mask

app/service/design/items/pipelines/painting.py

@@ -1,6 +1,5 @@
 import random
 
-# import boto3
 import cv2
 import numpy as np
 from PIL import Image
@@ -9,12 +8,6 @@ from app.service.utils.oss_client import oss_get_image
 from ..builder import PIPELINES
 
 
-# minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
-
-
-# s3 = boto3.client('s3', aws_access_key_id=S3_ACCESS_KEY, aws_secret_access_key=S3_AWS_SECRET_ACCESS_KEY, region_name=S3_REGION_NAME)
-
-
 @PIPELINES.register_module()
 class Painting(object):
     def __init__(self, painting_flag=True):

app/service/design/items/pipelines/scale.py

@@ -1,7 +1,9 @@
-from ..builder import PIPELINES
 import math
+
 import cv2
 
+from ..builder import PIPELINES
+
 
 @PIPELINES.register_module()
 class Scaling(object):

app/service/design/items/pipelines/split.py

@@ -1,11 +1,12 @@
 import logging
+
 import cv2
 import numpy as np
+from PIL import Image
 from cv2 import cvtColor, COLOR_BGR2RGBA
 
 from app.service.utils.generate_uuid import generate_uuid
 from ..builder import PIPELINES
-from PIL import Image
 from ...utils.conversion_image import rgb_to_rgba
 from ...utils.upload_image import upload_png_mask
 

app/service/design/items/shoes.py

@@ -1,14 +1,9 @@
-import io
-import logging
-import time
-
 import cv2
 import numpy as np
+from PIL import Image
 
 from .builder import ITEMS
 from .clothing import Clothing
-from PIL import Image
-
 from ..utils.conversion_image import rgb_to_rgba
 from ..utils.upload_image import upload_png_mask
 from ...utils.generate_uuid import generate_uuid

app/service/design/utils/conversion_image.py

@@ -19,5 +19,6 @@ def rgb_to_rgba(rgb_size, rgb_image, mask):
     rgba_image[:, :, 3] = alpha_channel
     return rgba_image
 
+
 if __name__ == '__main__':
-    image = open("")
+    image = open("")

app/service/design/utils/design_ensemble.py

@@ -8,12 +8,14 @@
 @detail  ：发起请求 获取推理结果
 """
 import logging
+
 import cv2
 import mmcv
 import numpy as np
-import tritonclient.http as httpclient
 import torch
 import torch.nn.functional as F
+import tritonclient.http as httpclient
+
 from app.core.config import *
 
 """

app/service/design/utils/synthesis_item.py

@@ -10,30 +10,13 @@
 import io
 import logging
 
-# import boto3
 import cv2
 import numpy as np
 from PIL import Image
-from minio import Minio
 
-from app.core.config import *
 from app.service.utils.generate_uuid import generate_uuid
 from app.service.utils.oss_client import oss_upload_image
 
-minio_client = Minio(
-    MINIO_URL,
-    access_key=MINIO_ACCESS,
-    secret_key=MINIO_SECRET,
-    secure=MINIO_SECURE)
-
-
-# s3 = boto3.client(
-#     's3',
-#     aws_access_key_id=S3_ACCESS_KEY,
-#     aws_secret_access_key=S3_AWS_SECRET_ACCESS_KEY,
-#     region_name=S3_REGION_NAME
-# )
-
 
 def positioning(all_mask_shape, mask_shape, offset):
     all_start = 0
@@ -176,4 +159,9 @@ def synthesis_single(front_image, back_image):
     result_image.save(image_data, format='PNG')
     image_data.seek(0)
     image_bytes = image_data.read()
-    return f"aida-results/{minio_client.put_object('aida-results', f'result_{generate_uuid()}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
+    # return f"aida-results/{minio_client.put_object('aida-results', f'result_{generate_uuid()}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
+    # oss upload
+    bucket_name = 'aida-results'
+    object_name = f'result_{generate_uuid()}.png'
+    req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+    return f"{bucket_name}/{object_name}"

app/service/utils/oss_client.py

@@ -63,7 +63,7 @@ if __name__ == '__main__':
     # url = "aida-users/87/print/956614a2-7e75-4fbe-9ed0-c1831e37a2c9-4-87.png"
     # url = "aida-users/89/single_logo/123-89.png"
     # url = "aida-users/89/product_image/string-89.png"
-    url = "aida-users/10/models/female/9c788f5b-b8c7-424c-b149-025aeb0bda51model.png"
+    url = "aida-clothing/mask/mask_773e270b-3369-11ef-abe4-b0dcefbff887.png"
     read_type = "PIL"
     if read_type == "cv2":
         img = oss_get_image(bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type)