feat : 代码梳理 移除所有敏感密钥 通过环境变量方式配置

app/service/design_batch/utils/MQ.py

@@ -2,16 +2,17 @@ import json
 
 import pika
 
-from app.core.config import RABBITMQ_PARAMS, BATCH_DESIGN_RABBITMQ_QUEUES
+from app.core.config import settings
+from app.core.rabbit_mq_config import RABBITMQ_PARAMS
 
 
 def publish_status(task_id, progress, result):
     connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
     channel = connection.channel()
-    channel.queue_declare(queue=BATCH_DESIGN_RABBITMQ_QUEUES, durable=True)
+    channel.queue_declare(queue=settings.BATCH_DESIGN_RABBITMQ_QUEUES, durable=True)
     message = {'task_id': task_id, 'progress': progress, "result": result}
     channel.basic_publish(exchange='',
-                          routing_key=BATCH_DESIGN_RABBITMQ_QUEUES,
+                          routing_key=settings.BATCH_DESIGN_RABBITMQ_QUEUES,
                           body=json.dumps(message),
                           properties=pika.BasicProperties(
                               delivery_mode=2,

app/service/design_batch/utils/design_ensemble.py

@@ -16,7 +16,7 @@ import torch
 import torch.nn.functional as F
 import tritonclient.http as httpclient
 
-from app.core.config import *
+from app.core.config import DESIGN_MODEL_URL, DESIGN_MODEL_NAME
 
 """
     keypoint
@@ -91,29 +91,29 @@ def seg_preprocess(img_path):
 
 
 # @ RunTime
-def get_seg_result(image_id, image):
+def get_seg_result(image):
     image, ori_shape = seg_preprocess(image)
     client = httpclient.InferenceServerClient(url=f"{DESIGN_MODEL_URL}")
     transformed_img = image.astype(np.float32)
     # 输入集
     inputs = [
-        httpclient.InferInput(SEGMENTATION['input'], transformed_img.shape, datatype="FP32")
+        httpclient.InferInput(DESIGN_MODEL_NAME, transformed_img.shape, datatype="FP32")
     ]
     inputs[0].set_data_from_numpy(transformed_img, binary_data=True)
     # 输出集
     outputs = [
-        httpclient.InferRequestedOutput(SEGMENTATION['output'], binary_data=True),
+        httpclient.InferRequestedOutput("seg_input__0", binary_data=True),
     ]
-    results = client.infer(model_name=SEGMENTATION['new_model_name'], inputs=inputs, outputs=outputs)
+    results = client.infer(model_name=DESIGN_MODEL_NAME, inputs=inputs, outputs=outputs)
     # 推理
     # 取结果
-    inference_output1 = results.as_numpy(SEGMENTATION['output'])
-    seg_result = seg_postprocess(int(image_id), inference_output1, ori_shape)
+    inference_output1 = results.as_numpy("seg_input__0")
+    seg_result = seg_postprocess(inference_output1, ori_shape)
     return seg_result
 
 
 # no cache
-def seg_postprocess(image_id, output, ori_shape):
+def seg_postprocess(output, ori_shape):
     seg_logit = F.interpolate(torch.tensor(output).float(), size=ori_shape, scale_factor=None, mode='bilinear', align_corners=False)
     seg_pred = seg_logit.cpu().numpy()
     return seg_pred[0]

app/service/design_batch/utils/organize.py

@@ -98,6 +98,8 @@ def calculate_start_point(keypoint_type, scale, clothes_point, body_point, offse
     """
     Align left
     Args:
+        offset:
+        resize_scale:
         keypoint_type: string, "waistband" | "shoulder" | "ear_point"
         scale: float
         clothes_point: dict{'left': [x1, y1, z1], 'right': [x2, y2, z2]}

app/service/design_batch/utils/progress.py

@@ -1,6 +1,6 @@
 import logging
 
-from app.service.design_fast.utils.redis_utils import Redis
+from app.service.utils.redis_utils import Redis
 
 logger = logging.getLogger(__name__)
 

app/service/design_batch/utils/redis_utils.py

@@ -1,99 +0,0 @@
-import redis
-
-from app.core.config import REDIS_HOST, REDIS_PORT
-
-
-class Redis(object):
-    """
-    redis数据库操作
-    """
-
-    @staticmethod
-    def _get_r():
-        host = REDIS_HOST
-        port = REDIS_PORT
-        db = 0
-        r = redis.StrictRedis(host, port, db)
-        return r
-
-    @classmethod
-    def write(cls, key, value, expire=None):
-        """
-        写入键值对
-        """
-        # 判断是否有过期时间，没有就设置默认值
-        if expire:
-            expire_in_seconds = expire
-        else:
-            expire_in_seconds = 100
-        r = cls._get_r()
-        r.set(key, value, ex=expire_in_seconds)
-
-    @classmethod
-    def read(cls, key):
-        """
-        读取键值对内容
-        """
-        r = cls._get_r()
-        value = r.get(key)
-        return value.decode('utf-8') if value else value
-
-    @classmethod
-    def hset(cls, name, key, value):
-        """
-        写入hash表
-        """
-        r = cls._get_r()
-        r.hset(name, key, value)
-
-    @classmethod
-    def hget(cls, name, key):
-        """
-        读取指定hash表的键值
-        """
-        r = cls._get_r()
-        value = r.hget(name, key)
-        return value.decode('utf-8') if value else value
-
-    @classmethod
-    def hgetall(cls, name):
-        """
-        获取指定hash表所有的值
-        """
-        r = cls._get_r()
-        return r.hgetall(name)
-
-    @classmethod
-    def delete(cls, *names):
-        """
-        删除一个或者多个
-        """
-        r = cls._get_r()
-        r.delete(*names)
-
-    @classmethod
-    def hdel(cls, name, key):
-        """
-		删除指定hash表的键值
-        """
-        r = cls._get_r()
-        r.hdel(name, key)
-
-    @classmethod
-    def expire(cls, name, expire=None):
-        """
-        设置过期时间
-        """
-        if expire:
-            expire_in_seconds = expire
-        else:
-            expire_in_seconds = 100
-        r = cls._get_r()
-        r.expire(name, expire_in_seconds)
-
-
-if __name__ == '__main__':
-    redis_client = Redis()
-    # print(redis_client.write(key="1230", value=0))
-    redis_client.write(key="1230", value=10)
-    # print(redis_client.read(key="1230"))

app/service/design_batch/utils/synthesis_item.py

@@ -13,9 +13,12 @@ import logging
 import cv2
 import numpy as np
 from PIL import Image
-
+from minio import Minio
+from app.core.config import settings
 from app.service.utils.generate_uuid import generate_uuid
-from app.service.utils.oss_client import oss_upload_image
+from app.service.utils.new_oss_client import oss_upload_image
+
+minio_client = Minio(settings.MINIO_URL, access_key=settings.MINIO_ACCESS, secret_key=settings.MINIO_SECRET, secure=settings.MINIO_SECURE)
 
 
 def positioning(all_mask_shape, mask_shape, offset):
@@ -136,7 +139,7 @@ def synthesis(data, size, basic_info):
         image_bytes = image_data.read()
         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)
+        oss_upload_image(oss_client=minio_client, bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
         return f"{bucket_name}/{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}"
 
@@ -177,11 +180,11 @@ def synthesis_single(front_image, back_image):
     # 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)
+    oss_upload_image(oss_client=minio_client, bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
     return f"{bucket_name}/{object_name}"
 
 
-def update_base_size_priority(layers, size):
+def update_base_size_priority(layers):
     # 计算透明背景图片的宽度
     min_x = min(info['position'][1] for info in layers)
     x_list = []

app/service/design_batch/utils/upload_image.py

@@ -12,7 +12,6 @@ import logging
 
 import cv2
 
-from app.core.config import *
 from app.service.utils.new_oss_client import oss_upload_image
 
 
@@ -25,15 +24,15 @@ def upload_png_mask(minio_client, front_image, object_name, mask=None):
             # 将掩模的3通道转换为4通道，白色部分不透明，黑色部分透明
             rgba_image = cv2.cvtColor(mask_inverted, cv2.COLOR_BGR2BGRA)
             rgba_image[rgba_image[:, :, 0] == 0] = [0, 0, 0, 0]
-            req = oss_upload_image(oss_client=minio_client, bucket=AIDA_CLOTHING, object_name=f"mask/mask_{object_name}.png", image_bytes=cv2.imencode('.png', rgba_image)[1])
-            mask_url = f"{AIDA_CLOTHING}/mask/mask_{object_name}.png"
+            req = oss_upload_image(oss_client=minio_client, bucket="aida-clothing", object_name=f"mask/mask_{object_name}.png", image_bytes=cv2.imencode('.png', rgba_image)[1])
+            mask_url = f"aida-clothing/mask/mask_{object_name}.png"
 
         image_data = io.BytesIO()
         front_image.save(image_data, format='PNG')
         image_data.seek(0)
         image_bytes = image_data.read()
-        req = oss_upload_image(oss_client=minio_client, bucket=AIDA_CLOTHING, object_name=f"image/image_{object_name}.png", image_bytes=image_bytes)
-        image_url = f"{AIDA_CLOTHING}/image/image_{object_name}.png"
+        req = oss_upload_image(oss_client=minio_client, bucket="aida-clothing", object_name=f"image/image_{object_name}.png", image_bytes=image_bytes)
+        image_url = f"aida-clothing/image/image_{object_name}.png"
         return front_image, image_url, mask_url
     except Exception as e:
         logging.warning(f"upload_png_mask runtime exception : {e}")