feat

fix  minio and s3

app/api/api_test.py

@@ -1,6 +1,6 @@
 import logging
 from fastapi import APIRouter
-from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES
+from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES, OSS
 from fastapi import FastAPI, HTTPException
 
 from app.schemas.response_template import ResponseModel
@@ -16,6 +16,7 @@ def test(id: int):
         "GI_RABBITMQ_QUEUES": GI_RABBITMQ_QUEUES,
         "GPI_RABBITMQ_QUEUES": GPI_RABBITMQ_QUEUES,
         "GRI_RABBITMQ_QUEUES": GRI_RABBITMQ_QUEUES,
+        "local_oss_server": OSS
     }
     logger.info(data)
     if id == 1:

app/service/attribute/service_att_recognition.py

@@ -11,12 +11,12 @@ from minio import Minio
 import tritonclient.http as httpclient
 from app.core.config import *
 from app.schemas.attribute_retrieve import AttributeRecognitionModel
+from app.service.utils.oss_client import oss_get_image
 
 
 class AttributeRecognition:
     def __init__(self, const, request_data):
-        self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
-        logging.info("实例化完成")
+        # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
         self.request_data = []
         for i, sketch in enumerate(request_data):
             self.request_data.append(
@@ -97,9 +97,10 @@ class AttributeRecognition:
         return res
 
     def get_image(self, url):
-        response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1])
-        img = np.frombuffer(response.data, np.uint8)  # 转成8位无符号整型
-        img = cv2.imdecode(img, cv2.IMREAD_COLOR)  # 解码
+        # response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1])
+        # img = np.frombuffer(response.data, np.uint8)  # 转成8位无符号整型
+        # img = cv2.imdecode(img, cv2.IMREAD_COLOR)  #
+        img = oss_get_image(bucket=url.split("/", 1)[0], object_name=url.split("/", 1)[1], data_type="cv2")
         img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
         return img
 

app/service/attribute/service_category_recognition.py

@@ -18,12 +18,13 @@ import torch
 
 from app.core.config import *
 from app.schemas.attribute_retrieve import CategoryRecognitionModel
+from app.service.utils.oss_client import oss_get_image
 
 
 class CategoryRecognition:
     def __init__(self, request_data):
         self.attr_type = pd.read_csv(CATEGORY_PATH)
-        self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
+        # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
         self.request_data = []
         self.triton_client = httpclient.InferenceServerClient(url=ATT_TRITON_URL)
         for sketch in request_data:
@@ -51,9 +52,10 @@ class CategoryRecognition:
     def get_image(self, url):
         # Get data of an object.
         # Read data from response.
-        response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1])
-        img = np.frombuffer(response.data, np.uint8)  # 转成8位无符号整型
-        img = cv2.imdecode(img, cv2.IMREAD_COLOR)  # 解码
+        # response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1])
+        # img = np.frombuffer(response.data, np.uint8)  # 转成8位无符号整型
+        # img = cv2.imdecode(img, cv2.IMREAD_COLOR)  # 解码
+        img = oss_get_image(bucket=url.split("/", 1)[0], object_name=url.split("/", 1)[1], data_type="cv2")
         img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
         return img
 

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

@@ -1,5 +1,6 @@
 import logging
 import time
+
 import numpy as np
 from pymilvus import MilvusClient
 
@@ -71,11 +72,8 @@ class KeypointDetection(object):
         ]
         try:
             client = MilvusClient(uri=MILVUS_URL, token=MILVUS_TOKEN, db_name=MILVUS_ALIAS)
-            start_time = time.time()
-            res = client.upsert(
-                collection_name=MILVUS_TABLE_KEYPOINT,
-                data=data,
-            )
+            # start_time = time.time()
+            res = client.upsert(collection_name=MILVUS_TABLE_KEYPOINT, data=data)
             # logging.info(f"save keypoint time : {time.time() - start_time}")
             client.close()
             return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist()))

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

@@ -1,6 +1,5 @@
 import io
 import logging
-import time
 
 import cv2
 import numpy as np
@@ -8,6 +7,7 @@ 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
 
 
@@ -70,11 +70,7 @@ class LoadImageFromFile(object):
 class LoadBodyImageFromFile(object):
     def __init__(self, body_path):
         self.body_path = body_path
-        self.minioClient = Minio(
-            f"{MINIO_URL}",
-            access_key=MINIO_ACCESS,
-            secret_key=MINIO_SECRET,
-            secure=MINIO_SECURE)
+        # self.minioClient = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
 
         # response = self.minioClient.get_object("aida-mannequins", "model_1693218345.2714431.png")
 
@@ -82,33 +78,33 @@ class LoadBodyImageFromFile(object):
     def __call__(self, result):
         result["image_url"] = result['body_path'] = self.body_path
         result["name"] = "mannequin"
-        if not result['image_url'].lower().endswith(".png"):
-            logging.info(1)
-            bucket = self.body_path.split("/", 1)[0]
-            object_name = self.body_path.split("/", 1)[1]
-            new_object_name = f'{object_name[:object_name.rfind(".")]}.png'
-            image = self.minioClient.get_object(bucket, object_name)
-            image = Image.open(io.BytesIO(image.data))
-            image = image.convert("RGBA")
-            data = image.getdata()
-            #
-            new_data = []
-            for item in data:
-                if item[0] >= 230 and item[1] >= 230 and item[2] >= 230:
-                    new_data.append((255, 255, 255, 0))
-                else:
-                    new_data.append(item)
-            image.putdata(new_data)
-            image_data = io.BytesIO()
-            image.save(image_data, format='PNG')
-            image_data.seek(0)
-            image_bytes = image_data.read()
-            image_path = f"{bucket}/{self.minioClient.put_object(bucket, new_object_name, io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
-            self.body_path = image_path
-            result["image_url"] = result['body_path'] = self.body_path
-        response = self.minioClient.get_object(self.body_path.split("/", 1)[0], self.body_path.split("/", 1)[1])
+        # if not result['image_url'].lower().endswith(".png"):
+        #     bucket = self.body_path.split("/", 1)[0]
+        #     object_name = self.body_path.split("/", 1)[1]
+        #     new_object_name = f'{object_name[:object_name.rfind(".")]}.png'
+        #     image = self.minioClient.get_object(bucket, object_name)
+        #     image = Image.open(io.BytesIO(image.data))
+        #     image = image.convert("RGBA")
+        #     data = image.getdata()
+        #     #
+        #     new_data = []
+        #     for item in data:
+        #         if item[0] >= 230 and item[1] >= 230 and item[2] >= 230:
+        #             new_data.append((255, 255, 255, 0))
+        #         else:
+        #             new_data.append(item)
+        #     image.putdata(new_data)
+        #     image_data = io.BytesIO()
+        #     image.save(image_data, format='PNG')
+        #     image_data.seek(0)
+        #     image_bytes = image_data.read()
+        #     image_path = f"{bucket}/{self.minioClient.put_object(bucket, new_object_name, io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
+        #     self.body_path = image_path
+        #     result["image_url"] = result['body_path'] = self.body_path
+        # response = self.minioClient.get_object(self.body_path.split("/", 1)[0], self.body_path.split("/", 1)[1])
         # put_image_time = time.time()
-        result['body_image'] = Image.open(io.BytesIO(response.read()))
+        # result['body_image'] = Image.open(io.BytesIO(response.read()))
+        result['body_image'] = oss_get_image(bucket=self.body_path.split("/", 1)[0], object_name=self.body_path.split("/", 1)[1], data_type="PIL")
         # logging.info(f"Image.open time is : {time.time() - put_image_time}")
         return result
 

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

@@ -1,19 +1,16 @@
 import random
-from io import BytesIO
+
 # 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.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)
+
+# 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)
 
@@ -56,17 +53,18 @@ class Painting(object):
 
     @staticmethod
     def get_gradient(bucket_name, object_name):
-        image_data = minio_client.get_object(bucket_name, object_name)
+        # image_data = minio_client.get_object(bucket_name, object_name)
         # image_data = s3.get_object(Bucket=bucket_name, Key=object_name)['Body']
 
         # 从数据流中读取图像
-        image_bytes = image_data.read()
+        # image_bytes = image_data.read()
 
         # 将图像数据转换为numpy数组
-        image_array = np.asarray(bytearray(image_bytes), dtype=np.uint8)
+        # image_array = np.asarray(bytearray(image_bytes), dtype=np.uint8)
 
         # 使用OpenCV解码图像数组
-        image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
+        # image = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
+        image = oss_get_image(bucket=bucket_name, object_name=object_name, data_type="cv2")
         return image
 
     @staticmethod
@@ -494,16 +492,20 @@ class PrintPainting(object):
         if not 'IfSingle' in print_dict.keys():
             print_dict['IfSingle'] = False
 
-        data = minio_client.get_object(print_dict['print_path_list'][0].split("/", 1)[0], print_dict['print_path_list'][0].split("/", 1)[1])
-        # data = s3.get_object(Bucket=print_dict['print_path_list'][0].split("/", 1)[0], Key=print_dict['print_path_list'][0].split("/", 1)[1])['Body']
+        # data = minio_client.get_object(print_dict['print_path_list'][0].split("/", 1)[0], print_dict['print_path_list'][0].split("/", 1)[1])
+        # data_bytes = BytesIO(data.read())
+        # image = Image.open(data_bytes)
+        # image_mode = image.mode
 
-        data_bytes = BytesIO(data.read())
-        image = Image.open(data_bytes)
-        image_mode = image.mode
+        bucket_name = print_dict['print_path_list'][0].split("/", 1)[0]
+        object_name = print_dict['print_path_list'][0].split("/", 1)[1]
+        image = oss_get_image(bucket=bucket_name, object_name=object_name, data_type="cv2")
         # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
-        if image_mode == "RGBA":
-            new_background = Image.new('RGB', image.size, (255, 255, 255))
-            new_background.paste(image, mask=image.split()[3])
+        if image.shape[2] == 4:
+            image_rgb = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
+            image_pil = Image.fromarray(image_rgb)
+            new_background = Image.new('RGB', image_pil.size, (255, 255, 255))
+            new_background.paste(image_pil, mask=image.split()[3])
             image = new_background
         print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
 
@@ -577,21 +579,30 @@ class PrintPainting(object):
 
     @staticmethod
     def read_image(image_url):
-        data = minio_client.get_object(image_url.split("/", 1)[0], image_url.split("/", 1)[1])
-        # data = s3.get_object(Bucket=image_url.split("/", 1)[0], Key=image_url.split("/", 1)[1])['Body']
-
-        data_bytes = BytesIO(data.read())
-        image = Image.open(data_bytes)
-        image_mode = image.mode
-        # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
-        if image_mode == "RGBA":
-            # new_background = Image.new('RGB', image.size, (255, 255, 255))
-            # new_background.paste(image, mask=image.split()[3])
-            # image = new_background
-            return image, image_mode
-        image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        image = oss_get_image(bucket=image_url.split("/", 1)[0], object_name=image_url.split("/", 1)[1], data_type="cv2")
+        if image.shape[2] == 4:
+            image_rgb = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
+            image = Image.fromarray(image_rgb)
+            image_mode = "RGBA"
+        else:
+            image_mode = "RGB"
         return image, image_mode
 
+        # data = minio_client.get_object(image_url.split("/", 1)[0], image_url.split("/", 1)[1])
+        # # data = s3.get_object(Bucket=image_url.split("/", 1)[0], Key=image_url.split("/", 1)[1])['Body']
+        #
+        # data_bytes = BytesIO(data.read())
+        # image = Image.open(data_bytes)
+        # image_mode = image.mode
+        # # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
+        # if image_mode == "RGBA":
+        #     # new_background = Image.new('RGB', image.size, (255, 255, 255))
+        #     # new_background.paste(image, mask=image.split()[3])
+        #     # image = new_background
+        #     return image, image_mode
+        # image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        # return image, "RGB"
+
     # @staticmethod
     # def read_image(image_url):
     #     response = requests.get(image_url)

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

@@ -41,7 +41,7 @@ class Split(object):
                 else:
                     back_mask = result['back_mask']
 
-                rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), result['final_image'], result['mask'])
+                rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), re4sult['final_image'], result['mask'])
                 result_front_image = np.zeros_like(rgba_image)
                 result_front_image[front_mask != 0] = rgba_image[front_mask != 0]
 

app/service/design_pre_processing/service.py

@@ -13,15 +13,12 @@ import io
 
 from app.core.config import *
 from app.service.design.utils.design_ensemble import get_keypoint_result
+from app.service.utils.oss_client import oss_get_image, oss_upload_image
 
 
 class DesignPreprocessing:
-    def __init__(self):
-        self.minio_client = Minio(
-            MINIO_URL,
-            access_key=MINIO_ACCESS,
-            secret_key=MINIO_SECRET,
-            secure=MINIO_SECURE)
+    # def __init__(self):
+    # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
 
     # @ RunTime
     def pipeline(self, image_list):
@@ -51,8 +48,9 @@ class DesignPreprocessing:
 
     def read_image(self, image_list):
         for obj in image_list:
-            file = self.minio_client.get_object(obj['image_url'].split("/", 1)[0], obj['image_url'].split("/", 1)[1]).data
-            image = cv2.imdecode(np.frombuffer(file, np.uint8), 1)
+            # file = self.minio_client.get_object(obj['image_url'].split("/", 1)[0], obj['image_url'].split("/", 1)[1]).data
+            # image = cv2.imdecode(np.frombuffer(file, np.uint8), 1)
+            image = oss_get_image(bucket=obj['image_url'].split("/", 1)[0], object_name=obj['image_url'].split("/", 1)[1], data_type="cv2")
             if len(image.shape) == 2:
                 image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
             elif image.shape[2] == 4:  # 如果是四通道 mask
@@ -125,7 +123,10 @@ class DesignPreprocessing:
             try:
                 # 覆盖到minio
                 image_bytes = cv2.imencode(".jpg", item['obj'])[1].tobytes()
-                self.minio_client.put_object(item['image_url'].split("/", 1)[0], item['image_url'].split("/", 1)[1], io.BytesIO(image_bytes), len(image_bytes), content_type="image/jpeg", )
+                # self.minio_client.put_object(item['image_url'].split("/", 1)[0], item['image_url'].split("/", 1)[1], io.BytesIO(image_bytes), len(image_bytes), content_type="image/jpeg", )
+                bucket_name = item['image_url'].split("/", 1)[0]
+                object_name = item['image_url'].split("/", 1)[1]
+                oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
                 print(f"Object '{item['image_url'].split('/', 1)[1]}' overwritten successfully.")
             except ResponseError as err:
                 print(f"Error: {err}")
@@ -165,36 +166,76 @@ class DesignPreprocessing:
     # @ RunTime
     def composing_image(self, image_list):
         for image in image_list:
-            if image['site'] == 'down':
-                image_width = image['obj'].shape[1]
-                waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1]
-                scale = 0.4
-                if waist_width / scale >= image['obj'].shape[1]:
-                    add_width = int((waist_width / scale - image_width) / 2)
-                    ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
-                    if IF_DEBUG_SHOW:
-                        cv2.imshow("composing_image", ret)
-                        cv2.waitKey(0)
-                    image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
-                    image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
-                else:
-                    image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes()
-                    image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+            ''' 比例相同 整合上下装代码'''
+            image_width = image['obj'].shape[1]
+            waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1]
+            scale = 0.4
+            if waist_width / scale >= image_width:
+                add_width = int((waist_width / scale - image_width) / 2)
+                ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
+                if IF_DEBUG_SHOW:
+                    cv2.imshow("composing_image", ret)
+                    cv2.waitKey(0)
+                image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
+                # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+                bucket_name = image['image_url'].split('/', 1)[0]
+                object_name = image['image_url'].split('/', 1)[1]
+                oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+                image['show_image_url'] = f"{bucket_name}/{object_name}"
             else:
-                scale = 0.4
-                image_width = image['obj'].shape[1]
-                waist_width = image['keypoint_result']['armpit_right'][1] - image['keypoint_result']['armpit_left'][1]
-                if waist_width / scale >= image_width:
-                    add_width = int((waist_width / scale - image_width) / 2)
-                    ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
-                    if IF_DEBUG_SHOW:
-                        cv2.imshow("composing_image", ret)
-                        cv2.waitKey(0)
-                    image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
-                    image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
-                else:
-                    image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes()
-                    image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+                image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes()
+                # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+                bucket_name = image['image_url'].split('/', 1)[0]
+                object_name = image['image_url'].split('/', 1)[1]
+                oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+                image['show_image_url'] = f"{bucket_name}/{object_name}"
+
+            # if image['site'] == 'down':
+            #     image_width = image['obj'].shape[1]
+            #     waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1]
+            #     scale = 0.4
+            #     if waist_width / scale >= image_width:
+            #         add_width = int((waist_width / scale - image_width) / 2)
+            #         ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
+            #         if IF_DEBUG_SHOW:
+            #             cv2.imshow("composing_image", ret)
+            #             cv2.waitKey(0)
+            #         image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
+            #         # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+            #         bucket_name = image['image_url'].split('/', 1)[0]
+            #         object_name = image['image_url'].split('/', 1)[1]
+            #         oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+            #         image['show_image_url'] = f"{bucket_name}/{object_name}"
+            #     else:
+            #         image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes()
+            #         # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+            #         bucket_name = image['image_url'].split('/', 1)[0]
+            #         object_name = image['image_url'].split('/', 1)[1]
+            #         oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+            #         image['show_image_url'] = f"{bucket_name}/{object_name}"
+            # else:
+            #     image_width = image['obj'].shape[1]
+            #     waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1]
+            #     scale = 0.4
+            #     if waist_width / scale >= image_width:
+            #         add_width = int((waist_width / scale - image_width) / 2)
+            #         ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
+            #         if IF_DEBUG_SHOW:
+            #             cv2.imshow("composing_image", ret)
+            #             cv2.waitKey(0)
+            #         image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
+            #         # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+            #         bucket_name = image['image_url'].split('/', 1)[0]
+            #         object_name = image['image_url'].split('/', 1)[1]
+            #         oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+            #         image['show_image_url'] = f"{bucket_name}/{object_name}"
+            #     else:
+            #         image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes()
+            #         # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
+            #         bucket_name = image['image_url'].split('/', 1)[0]
+            #         object_name = image['image_url'].split('/', 1)[1]
+            #         oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+            #         image['show_image_url'] = f"{bucket_name}/{object_name}"
         return image_list
 
     @staticmethod

app/service/generate_image/service_generate_image.py

@@ -10,22 +10,17 @@
 import json
 import logging
 import time
-from io import BytesIO
-
 import cv2
 import minio
 import redis
 import tritonclient.grpc as grpcclient
 import numpy as np
-from minio import Minio
 from tritonclient.utils import np_to_triton_dtype
-
 from app.core.config import *
 from app.schemas.generate_image import GenerateImageModel
-from app.service.generate_image.utils.adjust_contrast import adjust_contrast
 from app.service.generate_image.utils.image_processing import remove_background, stain_detection, generate_category_recognition, autoLevels, luminance_adjust, face_detect_pic
-from app.service.generate_image.utils.upload_sd_image import upload_png_sd, upload_stain_png_sd
-from app.service.utils.oss_client import get_image
+from app.service.generate_image.utils.upload_sd_image import upload_png_sd
+from app.service.utils.oss_client import oss_get_image
 
 logger = logging.getLogger()
 
@@ -70,7 +65,7 @@ class GenerateImage:
             # image_cv2 = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
             # image_rbg = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB)
 
-            image_cv2 = get_image(object_name=image_url, data_type="cv2")
+            image_cv2 = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url, data_type="cv2")
             image_rbg = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB)
             image = cv2.resize(image_rbg, (1024, 1024))
         except minio.error.S3Error:

app/service/super_resolution/service.py

@@ -1,17 +1,15 @@
-import io
+import json
 import logging
 import time
-import minio.error
-import redis
-import json
 import cv2
+import minio.error
 import numpy as np
+import redis
 import torch
 import tritonclient.grpc as grpcclient
-from minio import Minio
 from app.core.config import *
 from app.schemas.super_resolution import SuperResolutionModel
-from app.service.utils.decorator import RunTime
+from app.service.utils.oss_client import oss_get_image, oss_upload_image
 
 logger = logging.getLogger()
 
@@ -24,7 +22,7 @@ class SuperResolution:
         self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:]
         self.sr_image_url = data.sr_image_url
         self.sr_xn = data.sr_xn
-        self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
+        # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
         self.redis_client.set(self.tasks_id, json.dumps({'status': 'PENDING', 'message': "pending", 'data': ''}))
         self.redis_client.expire(self.tasks_id, 600)
         self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
@@ -33,16 +31,25 @@ class SuperResolution:
     # @RunTime
     def read_image(self):
         try:
-            image_data = self.minio_client.get_object(self.sr_image_url.split("/", 1)[0], self.sr_image_url.split("/", 1)[1])
+            img = oss_get_image(bucket=self.sr_image_url.split("/", 1)[0], object_name=self.sr_image_url.split("/", 1)[1], data_type="cv2")
         except minio.error.S3Error as e:
             sr_data = json.dumps({'tasks_id': self.tasks_id, 'status': 'ERROR', 'message': f'{e}'})
             self.channel.basic_publish(exchange='', routing_key=SR_RABBITMQ_QUEUES, body=sr_data)
             logger.info(f" [x] Sent {sr_data}")
             raise FileNotFoundError(f"Image '{self.sr_image_url.split('/', 1)[1]}' not found in bucket '{self.sr_image_url.split('/', 1)[0]}'")
-        img = np.frombuffer(image_data.data, np.uint8)  # 转成8位无符号整型
-        img = cv2.imdecode(img, cv2.IMREAD_COLOR).astype(np.float32) / 255.  # 解码
         return img
 
+        # try:
+        #     image_data = self.minio_client.get_object(self.sr_image_url.split("/", 1)[0], self.sr_image_url.split("/", 1)[1])
+        # except minio.error.S3Error as e:
+        #     sr_data = json.dumps({'tasks_id': self.tasks_id, 'status': 'ERROR', 'message': f'{e}'})
+        #     self.channel.basic_publish(exchange='', routing_key=SR_RABBITMQ_QUEUES, body=sr_data)
+        #     logger.info(f" [x] Sent {sr_data}")
+        #     raise FileNotFoundError(f"Image '{self.sr_image_url.split('/', 1)[1]}' not found in bucket '{self.sr_image_url.split('/', 1)[0]}'")
+        # img = np.frombuffer(image_data.data, np.uint8)  # 转成8位无符号整型
+        # img = cv2.imdecode(img, cv2.IMREAD_COLOR).astype(np.float32) / 255.  # 解码
+        # return img
+
     def read_tasks_status(self):
         status_data = json.loads(self.redis_client.get(self.tasks_id))
         logging.info(f"{self.tasks_id} ===> {status_data}")
@@ -101,8 +108,10 @@ class SuperResolution:
     def upload_img_sr(self, image):
         try:
             image_bytes = cv2.imencode('.jpg', image)[1].tobytes()
-            res = self.minio_client.put_object(f'{SR_MINIO_BUCKET}', f'{self.user_id}/sr/output/{self.tasks_id}.jpg', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png')
-            image_url = f"aida-users/{res.object_name}"
+            # res = self.minio_client.put_object(f'{SR_MINIO_BUCKET}', f'{self.user_id}/sr/output/{self.tasks_id}.jpg', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png')
+            object_name = f'{self.user_id}/sr/output/{self.tasks_id}.jpg'
+            oss_upload_image(bucket=SR_MINIO_BUCKET, object_name=object_name, image_bytes=image_bytes)
+            image_url = f"{SR_MINIO_BUCKET}/{object_name}"
             return image_url
         except Exception as e:
             logger.warning(f"upload_png_mask runtime exception : {e}")

app/service/utils/oss_client.py

@@ -15,8 +15,8 @@ logger = logging.getLogger()
 
 #  获取图片
 def oss_get_image(bucket, object_name, data_type):
+    # cv2 默认全通道读取
     image_object = None
-
     try:
         if OSS == "minio":
             oss_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
@@ -24,11 +24,10 @@ def oss_get_image(bucket, object_name, data_type):
         else:
             oss_client = boto3.client('s3', aws_access_key_id=S3_ACCESS_KEY, aws_secret_access_key=S3_AWS_SECRET_ACCESS_KEY, region_name=S3_REGION_NAME)
             image_data = oss_client.get_object(Bucket=bucket, Key=object_name)['Body']
-
         if data_type == "cv2":
             image_bytes = image_data.read()
             image_array = np.frombuffer(image_bytes, np.uint8)  # 转成8位无符号整型
-            image_object = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
+            image_object = cv2.imdecode(image_array, cv2.IMREAD_UNCHANGED)
         else:
             data_bytes = BytesIO(image_data.read())
             image_object = Image.open(data_bytes)
@@ -56,11 +55,12 @@ if __name__ == '__main__':
     # url = "aida-collection-element/11523/Moodboard/f60af0d2-94c2-48f9-90ff-74b8e8a481b5.jpg"
     # url = "aida-sys-image/images/female/outwear/0628000054.jpg"
     # url = "aida-users/89/product_image/string-89.png"
-    # url = "aida-users/89/single_logo/123-89.png"
+    url = "aida-users/89/single_logo/123-89.png"
     # url = 'aida-users/89/relight_image/123-89.png'
     # url = 'aida-users/89/relight_image/123-89.png'
-    url = 'aida-users/89/relight_image/123-89.png'
-    read_type = "PIL"
+    # url = 'aida-users/89/relight_image/123-89.png'
+    # url = "aida-users/89/sketchboard/female/Dress/e6724ab7-8d3f-4677-abe0-c3e42ab7af85.jpeg"
+    read_type = "cv2"
     if read_type == "cv2":
         img = oss_get_image(bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type)
         cv2.imshow("", img)