attribute 字段名规范

.gitignore

@@ -131,3 +131,4 @@ uwsgi
 app/logs
 *.log
 *.jpg
+*.zip

app/api/api_similar_match.py

@@ -0,0 +1,25 @@
+import logging
+import time
+
+from fastapi import APIRouter
+
+from app.schemas.similar_match import SimilarMatchMItem
+from app.service.similar_match.service import SimilarMatch
+from app.service.utils.decorator import RunTime
+
+logger = logging.getLogger()
+router = APIRouter()
+
+
+@RunTime
+@router.post("similar_match")
+def similar_match(request_item: SimilarMatchMItem):
+    try:
+        if request_item.result_number <= 0:
+            raise KeyError("result number can't be less than 0")
+        service = SimilarMatch(request_item)
+        search_response = service.match_features()
+        return {"message": "ok", "data": search_response}
+    except KeyError as e:
+        logger.warning(str(e))
+        return {"message": "result number can't be less than 0", "data": []}

app/schemas/similar_match.py

@@ -0,0 +1,6 @@
+from pydantic import BaseModel
+
+
+class SimilarMatchMItem(BaseModel):
+    image_path: str
+    result_number: int

app/service/attribute_recognition/const_debug.py

@@ -0,0 +1,139 @@
+import torch
+
+device = torch.device('cuda')
+top_discription_list = [r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\1_top_length.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\2_top_type.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\3_top_Sleeve_length.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\4_top_Sleeve_shape.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\5_top_Sleeve_shoulder.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\6_top_Neckline.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\7_outer_Print.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\8_outer_Material.csv',
+                        #   r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\9_top_Material.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\9_top_Softness.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\10_top_Design.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\11_top_OPType.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\12_top_Silhouette.csv',
+                        r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\top\7_top_Collar.csv']
+
+top_model_list = ['top_length',
+                  'top_type',
+                  'top_Sleeve_length',
+                  'top_Sleeve_shape',
+                  'top_Sleeve_shoulder',
+                  'top_Neckline',
+                  'top_print',
+                  'top_material',
+                  'top_Softness',
+                  'top_Design',
+                  'top_optype',
+                  'top_Silhouette',
+                  'top_Collar'
+                  ]
+
+bottom_discription_list = [
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\2_bottom_subtype.csv',
+    #    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\3_bottom_structure.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\3_bottom_length.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\7_outer_Print.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\8_outer_Material.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\5_bottom_Softness.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\8_bottom_Silhouette.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\7_bottom_OPType.csv',
+    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\bottom\6_bottom_Design.csv']
+
+bottom_model_list = [
+    'bottom_sub-Type',
+    'bottom_length',
+    'bottom_print',
+    'bottom_material',
+    'bottom_Softness_B',
+    'bottom_Silhouette_B',
+    'bottom_OPType_B',
+    'bottom_design']
+
+outwear_discription_list = [r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\1_outer_length.csv',
+                            #    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\2_outer_type.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\3_outer_sleeve_length.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\4_outer_sleeve_shape.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\5_outer_sleeve_shoulder.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\6_outer_Collar.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\7_outer_Print.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\8_outer_Material.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\9_outer_Softness.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\10_outer_Design.csv',
+                            #    r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\11_outer_opening.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\12_outer_OPType.csv',
+                            r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\outwear\13_outer_Silhouette.csv', ]
+
+outwear_model_list = ['outwear_outer_length',
+                      #   'outwear_2_outer_type',
+                      'outwear_outer_sleeve_length',
+                      'outwear_outer_sleeve_shape',
+                      'outwear_outer_sleeve_shoulder',
+                      'outwear_outer_collar',
+                      'outwear_print',
+                      'outwear_material',
+                      'outwear_outer_softness',
+                      'outwear_outer_design',
+                      #   'outwear_11_outer_opening',
+                      'outwear_outer_optype',
+                      'outwear_outer_silhouette']
+
+jumpsuit_discription_list = [r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\1_jumsuit_length.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\2_jumpsuit_Sleeve_length.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\3_jumpsuit_Sleeve_shape.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\4_jumpsuit_Sleeve_shoulder.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\5_jumpsuit_Neckline.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\6_jumpsuit_Collar.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\7_jumpsuit_Print.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\8_jumpsuit_Material.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\9_jumpsuit_Softness.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\10_jumsuit_design.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\11_jumpsuit_OPType.csv',
+                             r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\jumpsuit\12_jumpsuit_subtype.csv']
+
+jumpsuit_model_list = ['jumpsuit_length',
+                       'jumpsuit_sleeve_length',
+                       'jumpsuit_sleeve_shape',
+                       'jumpsuit_sleeve_shoulder',
+                       'jumpsuit_neckline',
+                       'jumpsuit_collar',
+                       'jumpsuit_print',
+                       'jumpsuit_material',
+                       'jumpsuit_softness',
+                       'jumpsuit_design',
+                       'jumpsuit_optype',
+                       'jumpsuit_subtype']
+
+dress_discription_list = [r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\1_dress_length.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\3_top_Sleeve_length.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\4_top_Sleeve_shape.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\5_top_Sleeve_shoulder.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\ori5_dress_Neckline.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\7_outer_Print.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\7_top_Collar.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\8_outer_Material.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\9_dress_Design.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\9_top_Softness.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\11_dress_Silhouette.csv',
+                          # r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\11_top_OPType.csv',
+                          r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\dress\12_dress_type.csv']
+
+dress_model_list = ['dress_length',
+                    'dress_sleeve_length',
+                    'dress_sleeve_shape',
+                    'dress_sleeve_shoulder',
+                    'dress_neckline',
+                    'dress_print',
+                    'dress_collar',
+                    'dress_material',
+                    'dress_design',
+                    'dress_softness',
+                    'dress_silohouette12',
+                    #   'dress_'
+                    'dress_type'
+                    ]
+
+category_discription = r'E:\workspace\trinity_client_mixi\app\service\attribute_recognition\discriptor\category\category_dis.csv'
+category_model = 'category'

app/service/outfit_matcher/test_param/test.json

@@ -0,0 +1,19 @@
+{
+  "topk": 1,
+  "max_outfits": 5,
+  "is_best": true,
+  "query": [
+    {
+      "image_path": "mi-tu/26/BOTTOM/PANTS/MKTS27000_0BLK.jpg/3f4676db-98a1-44d4-947f-9d1f59828629.jpg",
+      "item_name": "MKTS27000",
+      "semantic_category": "BOTTOM/PANTS"
+    }
+  ],
+  "database": [
+    {
+      "image_path": "mi-tu/26/TOP/BLOUSE/MKTS27002_0WHT.jpg/131cc29e-8f70-4134-a0e8-82f826b00058.jpg",
+      "item_name": "MKTS27002",
+      "semantic_category": "TOP/BLOUSE"
+    }
+  ]
+}

app/service/similar_match/service.py

@@ -0,0 +1,110 @@
+import io
+import json
+
+import numpy as np
+import tritonclient.http as httpclient
+from PIL import Image
+from minio import Minio
+from pymilvus import MilvusClient
+
+from app.core.config import *
+from torchvision import transforms
+
+from app.schemas.similar_match import SimilarMatchMItem
+from app.service.utils.decorator import RunTime
+
+
+class SimilarMatch:
+    def __init__(self, request_data):
+        self.minio_client = Minio(
+            f"{MINIO_IP}:{MINIO_PORT}",
+            access_key=MINIO_ACCESS,
+            secret_key=MINIO_SECRET,
+            secure=MINIO_SECURE)
+        self.triton_client = httpclient.InferenceServerClient(url=f"{OM_TRITON_IP}:{OM_TRITON_PORT}")
+        self.image_path = request_data.image_path
+        self.result_number = request_data.result_number
+        self.features = self.get_features()
+
+    @staticmethod
+    def resize_image(img):
+        """
+        Args:
+            img: ndarray (height, width, channel)
+        """
+        image_transforms = transforms.Compose([
+            transforms.Resize(112),
+            transforms.CenterCrop(112),
+            transforms.ToTensor(),
+            transforms.Normalize(mean=[0.485, 0.456, 0.406],
+                                 std=[0.229, 0.224, 0.225]),
+        ])
+        resized_img = image_transforms(img).numpy()
+        return resized_img
+
+    def load_image(self, img_path):
+        # 从 MinIO 中获取对象（图像文件）
+        image_data = self.minio_client.get_object(img_path.split("/", 1)[0], img_path.split("/", 1)[1])
+        # 读取图像数据并转换为 PIL 图像对象
+        pil_image = Image.open(io.BytesIO(image_data.data)).convert("RGB")
+        # 将 PIL 图像转换为 NumPy 数组
+        # image_array = np.array(pil_image)
+        return pil_image
+
+    def preprocess(self, img_path):
+        image = self.load_image(img_path)
+        image = self.resize_image(image)
+        image = np.stack([[image]], axis=0)
+
+        category = np.stack([[1, 6]], axis=0)
+
+        mask = np.zeros((1, 1), dtype=np.float32)
+        return image, category, mask
+
+    def get_features(self):
+        image, category, mask = self.preprocess(self.image_path)
+        # 输入集
+        inputs = [
+            httpclient.InferInput("input__0", image.shape, datatype="FP32"),
+            httpclient.InferInput("input__1", category.shape, datatype="INT16"),
+            httpclient.InferInput("input__2", mask.shape, datatype="FP32"),
+        ]
+        inputs[0].set_data_from_numpy(image.astype(np.float32), binary_data=True)
+        inputs[1].set_data_from_numpy(category.astype(np.int16), binary_data=True)
+        inputs[2].set_data_from_numpy(mask.astype(np.float32), binary_data=True)
+        # 输出集
+        outputs = [
+            httpclient.InferRequestedOutput("output__0", binary_data=True),
+            httpclient.InferRequestedOutput("output__1", binary_data=True)
+        ]
+        results = self.triton_client.infer(model_name="outfit_matcher_type_aware", inputs=inputs, outputs=outputs)
+        # 推理
+        # 取结果
+        features = results.as_numpy("output__1")  # Shape (N, 64)
+        return features
+
+    @RunTime
+    def match_features(self):
+        # 连接milvus
+        # 连接milvus
+        client = MilvusClient(uri="http://10.1.1.240:19530", db_name="mixi")
+        try:
+            search_response = client.search(
+                collection_name="mixi_outfit",  # Replace with the actual name of your collection
+                # Replace with your query vector
+                data=[self.features[0]],
+                limit=self.result_number,  # Max. number of search results to return
+                output_fields=["id", "image_path"],  # Search parameters
+            )
+            return search_response
+        finally:
+            client.close()
+
+
+if __name__ == '__main__':
+    request_data = SimilarMatchMItem(image_path="test/top/test_top1.jpg", result_number=1)
+
+    service = SimilarMatch(request_data)
+    search_response = service.match_features()
+
+    print(json.dumps(search_response, indent=4))