版本变更V3.35将图像的处理统一更换到新表当中

docker-compose.yml

@@ -1,4 +1,3 @@
-version: '3.8'
 
 services:
   db:

inventory-backend/.dockerignore

@@ -1,6 +1,12 @@
-venv/
-__pycache__/
+.git
+.idea
+__pycache__
 *.pyc
-.git/
+*.pyo
+venv
+.venv
+env
+uploads
+pgdata
 .env
-pgdata/
+simhei.ttf

inventory-backend/app/api/v1/common/image_search.py

@@ -19,6 +19,14 @@ from app.models.base import MaterialBase
 # 注册蓝图
 image_search_bp = Blueprint('image_search', __name__)
 
+# ============================================================================
+# 可配置参数
+# ============================================================================
+# 以图搜图相似度阈值：余弦距离必须小于此值（距离越小越相似）
+# 即余弦相似度 = 1 - 距离，必须 > (1 - SIMILARITY_THRESHOLD)
+# 默认 0.25 对应余弦相似度 > 0.75
+SIMILARITY_DISTANCE_THRESHOLD = 0.40
+
 
 # ============================================================================
 # POST /api/v1/common/image-search
@@ -87,27 +95,80 @@ def image_search():
         ie.module_name,
         ie.target_id,
         ie.image_url,
-        (1 - (ie.embedding <=> :query_vector)) AS similarity
+        (1 - (ie.embedding <=> :query_vector)) AS similarity,
+        (ie.embedding <=> :query_vector)        AS distance
     FROM image_embeddings ie
     WHERE ie.embedding IS NOT NULL
+      AND (ie.embedding <=> :query_vector) < :distance_threshold
     ORDER BY ie.embedding <=> :query_vector
     LIMIT 200
 """)
 
-        raw_records = db.session.execute(sql, {"query_vector": query_vector_str}).fetchall()
+        raw_records = db.session.execute(sql, {
+            "query_vector": query_vector_str,
+            "distance_threshold": SIMILARITY_DISTANCE_THRESHOLD
+        }).fetchall()
         if not raw_records:
-            return jsonify({"code": 200, "data": []})
+            return jsonify({"code": 200, "data": [], "msg": "未找到相似图片（阈值过滤后）"})
 
-        # 按 (module_name, target_id) 去重，每业务记录只保留最相似的那张图
-        seen = {}
+        # ---------------------------------------------------------
+        # Step 1: 初步去重（同入库单只保留最相似的图片）
+        # ---------------------------------------------------------
+        first_img_seen = {}
+        unique_records = []
         for row in raw_records:
             key = (row.module_name, row.target_id)
-            if key not in seen:
-                seen[key] = row
+            if key not in first_img_seen:
+                first_img_seen[key] = True
+                unique_records.append(row)
 
-        # 批量回填业务数据
+        # ---------------------------------------------------------
+        # Step 2: 按物料维度去重（相同物料只保留第一条 = 相似度最高的那条）
+        # ---------------------------------------------------------
         target_ids_by_module = {}
-        for row in seen.values():
+        for row in unique_records:
+            target_ids_by_module.setdefault(row.module_name, []).append(row.target_id)
+
+        # 查询每条记录的 base_id（跨 stock_buy/semi/product/material_base）
+        base_id_map = {}
+
+        for module in ('stock_buy', 'stock_semi', 'stock_product'):
+            if module not in target_ids_by_module:
+                continue
+            ids = target_ids_by_module[module]
+            ModelCls = StockBuy if module == 'stock_buy' else (StockSemi if module == 'stock_semi' else StockProduct)
+            id_col = getattr(ModelCls, 'id')
+            base_col = getattr(ModelCls, 'base_id')
+
+            rows = (
+                db.session.query(id_col, base_col)
+                .outerjoin(MaterialBase, base_col == MaterialBase.id)
+                .filter(id_col.in_(ids))
+                .all()
+            )
+            for rec_id, base_id in rows:
+                base_id_map[(module, rec_id)] = base_id
+
+        if 'material_base' in target_ids_by_module:
+            for rec_id in target_ids_by_module['material_base']:
+                base_id_map[('material_base', rec_id)] = rec_id
+
+        # 按 base_id 去重：相同物料只保留第一张图
+        material_seen = {}
+        final_records = []
+        for row in unique_records:
+            base_id = base_id_map.get((row.module_name, row.target_id))
+            if base_id is not None and base_id in material_seen:
+                continue
+            if base_id is not None:
+                material_seen[base_id] = True
+            final_records.append(row)
+
+        # ---------------------------------------------------------
+        # Step 3: 批量回填业务数据（基于去重后的 final_records）
+        # ---------------------------------------------------------
+        target_ids_by_module = {}
+        for row in final_records:
             target_ids_by_module.setdefault(row.module_name, []).append(row.target_id)
 
         business_map = {}
@@ -205,9 +266,9 @@ def image_search():
                     'url': '/material/index',
                 }
 
-        # 组装最终返回
+        # 组装最终返回（基于 final_records，按相似度从高到低）
         results = []
-        for row in seen.values():
+        for row in final_records:
             key = (row.module_name, row.target_id)
             biz = business_map.get(key, {})
             raw_url = row.image_url or ''

inventory-backend/app/services/inbound/base_service.py

@@ -561,13 +561,20 @@ class MaterialBaseService:
             db.session.add(new_material)
             db.session.flush()  # 获取 new_material.id
 
-            # 提取产品图向量到独立表（失败不影响业务）
+            # 先提交主事务，图片向量异步后台提取
+            db.session.commit()
+
             image_list = data.get('generalImage', [])
             if isinstance(image_list, list) and image_list:
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_MATERIAL_BASE, new_material.id, image_list
+                from flask import current_app
+                from app.utils.executor import run_embedding_task
+                run_embedding_task(
+                    ImageEmbeddingService.save_embeddings_background,
+                    current_app._get_current_object(),
+                    ImageEmbeddingService.MODULE_MATERIAL_BASE,
+                    new_material.id,
+                    image_list
                 )
-            db.session.commit()
             return new_material
 
         except Exception as e:
@@ -597,9 +604,16 @@ class MaterialBaseService:
             if 'generalImage' in data:
                 new_photo_list = data['generalImage']
                 material.product_image = json.dumps(new_photo_list)
-                # 保存向量到独立表（全量替换）
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_MATERIAL_BASE, material.id, new_photo_list
+                # 立即触发异步向量提取，不阻塞主事务提交
+                if isinstance(new_photo_list, list) and new_photo_list:
+                    from flask import current_app
+                    from app.utils.executor import run_embedding_task
+                    run_embedding_task(
+                        ImageEmbeddingService.save_embeddings_background,
+                        current_app._get_current_object(),
+                        ImageEmbeddingService.MODULE_MATERIAL_BASE,
+                        material.id,
+                        new_photo_list
                     )
             else:
                 material.product_image = None

inventory-backend/app/services/inbound/buy_service.py

@@ -183,13 +183,20 @@ class BuyInboundService:
             db.session.add(new_stock)
             db.session.flush()  # 获取 new_stock.id
 
-            # 提取到货图片向量到新表（失败不影响业务）
+            # 先提交主事务（入库单必须落盘），图片向量异步后台提取
+            db.session.commit()
+
             photo_list = data.get('arrival_photo', [])
             if isinstance(photo_list, list) and photo_list:
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_BUY, new_stock.id, photo_list
+                from flask import current_app
+                from app.utils.executor import run_embedding_task
+                run_embedding_task(
+                    ImageEmbeddingService.save_embeddings_background,
+                    current_app._get_current_object(),
+                    ImageEmbeddingService.MODULE_STOCK_BUY,
+                    new_stock.id,
+                    photo_list
                 )
-            db.session.commit()
             return new_stock
         except Exception as e:
             db.session.rollback()
@@ -254,9 +261,16 @@ class BuyInboundService:
             if 'arrival_photo' in data:
                 new_photo_list = data['arrival_photo']
                 stock.arrival_photo = json.dumps(new_photo_list)
-                # 保存向量到独立表（全量替换）
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_BUY, stock.id, new_photo_list
+                # 立即触发异步向量提取，不阻塞主事务提交
+                if isinstance(new_photo_list, list) and new_photo_list:
+                    from flask import current_app
+                    from app.utils.executor import run_embedding_task
+                    run_embedding_task(
+                        ImageEmbeddingService.save_embeddings_background,
+                        current_app._get_current_object(),
+                        ImageEmbeddingService.MODULE_STOCK_BUY,
+                        stock.id,
+                        new_photo_list
                     )
             else:
                 stock.arrival_photo = None

inventory-backend/app/services/inbound/product_service.py

@@ -189,12 +189,19 @@ class ProductInboundService:
             db.session.add(new_stock)
             db.session.flush()  # 获取 new_stock.id
 
-            # 提取产品图片向量到独立表（失败不影响业务）
-            if isinstance(photo_list, list) and photo_list:
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_PRODUCT, new_stock.id, photo_list
-                )
+            # 先提交主事务，图片向量异步后台提取
             db.session.commit()
+
+            if isinstance(photo_list, list) and photo_list:
+                from flask import current_app
+                from app.utils.executor import run_embedding_task
+                run_embedding_task(
+                    ImageEmbeddingService.save_embeddings_background,
+                    current_app._get_current_object(),
+                    ImageEmbeddingService.MODULE_STOCK_PRODUCT,
+                    new_stock.id,
+                    photo_list
+                )
             return new_stock
         except Exception as e:
             db.session.rollback()
@@ -225,9 +232,16 @@ class ProductInboundService:
             if 'product_photo' in data:
                 new_photo_list = data['product_photo']
                 stock.product_photo = json.dumps(new_photo_list)
-                # 保存向量到独立表（全量替换）
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_PRODUCT, stock.id, new_photo_list
+                # 立即触发异步向量提取，不阻塞主事务提交
+                if isinstance(new_photo_list, list) and new_photo_list:
+                    from flask import current_app
+                    from app.utils.executor import run_embedding_task
+                    run_embedding_task(
+                        ImageEmbeddingService.save_embeddings_background,
+                        current_app._get_current_object(),
+                        ImageEmbeddingService.MODULE_STOCK_PRODUCT,
+                        stock.id,
+                        new_photo_list
                     )
             else:
                 stock.product_photo = None

inventory-backend/app/services/inbound/semi_service.py

@@ -226,12 +226,19 @@ class SemiInboundService:
             db.session.add(new_stock)
             db.session.flush()  # 获取 new_stock.id
 
-            # 提取到货图片向量到独立表（失败不影响业务）
-            if isinstance(arrival_list, list) and arrival_list:
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_SEMI, new_stock.id, arrival_list
-                )
+            # 先提交主事务，图片向量异步后台提取
             db.session.commit()
+
+            if isinstance(arrival_list, list) and arrival_list:
+                from flask import current_app
+                from app.utils.executor import run_embedding_task
+                run_embedding_task(
+                    ImageEmbeddingService.save_embeddings_background,
+                    current_app._get_current_object(),
+                    ImageEmbeddingService.MODULE_STOCK_SEMI,
+                    new_stock.id,
+                    arrival_list
+                )
             return new_stock
         except Exception as e:
             db.session.rollback()
@@ -280,9 +287,16 @@ class SemiInboundService:
             if 'arrival_photo' in data:
                 new_photo_list = data['arrival_photo']
                 stock.arrival_photo = json.dumps(new_photo_list)
-                # 保存向量到独立表（全量替换）
-                ImageEmbeddingService.save_embeddings(
-                    ImageEmbeddingService.MODULE_STOCK_SEMI, stock.id, new_photo_list
+                # 立即触发异步向量提取，不阻塞主事务提交
+                if isinstance(new_photo_list, list) and new_photo_list:
+                    from flask import current_app
+                    from app.utils.executor import run_embedding_task
+                    run_embedding_task(
+                        ImageEmbeddingService.save_embeddings_background,
+                        current_app._get_current_object(),
+                        ImageEmbeddingService.MODULE_STOCK_SEMI,
+                        stock.id,
+                        new_photo_list
                     )
             else:
                 stock.arrival_photo = None

inventory-backend/app/utils/ai_vision.py

@@ -9,6 +9,7 @@ import time
 import numpy as np
 from PIL import Image
 import onnxruntime as ort
+import cv2
 
 # ============================================================================
 # 全局模型单例（项目启动时加载一次）
@@ -48,33 +49,115 @@ IMAGENET_STD = [0.229, 0.224, 0.225]
 # 模型输入尺寸
 INPUT_SIZE = 224
 
+# ============================================================================
+# 背景去除配置：HSV 色彩空间阈值
+# ============================================================================
+# OpenCV HSV: H∈[0,180], S∈[0,255], V∈[0,255]
+# 注意：OpenCV 中 H 通道范围是 0-180（是 OpenCV 自己的标准，和美术的 0-360 对应）
 
-def _center_crop_and_resize(image: Image.Image) -> Image.Image:
+# 绿色背景阈值（工业绿幕常用色）
+# H: 35~85 对应绿色谱（浅绿到深绿）
+# S: 低饱和度（35）到高饱和度（255）
+# V: 明暗均可（30~255）
+BG_GREEN_LOWER = np.array([35, 35, 30])
+BG_GREEN_UPPER = np.array([90, 255, 255])
+
+# 白色/浅色背景阈值（高明度、低饱和度区域）
+# H: 不限制（0~180），只看 S 和 V
+# S: 很低的饱和度（0~35）→ 接近纯灰/白色
+# V: 高明度（180~255）
+BG_WHITE_LOWER = np.array([0, 0, 180])
+BG_WHITE_UPPER = np.array([180, 40, 255])
+
+# 中性灰填充色（BGR → 转换后 RGB 也是 128,128,128）
+NEUTRAL_GRAY_BGR = (128, 128, 128)
+
+
+def _remove_background(image: Image.Image) -> Image.Image:
     """
-    CLIP 官方预处理：中心裁剪抗干扰
-    - 将图片最短边缩放到 224
-    - 从正中间切取 224x224 区域
+    利用 OpenCV HSV 色彩空间识别并替换背景为中性灰
+
+    支持两种背景类型：
+    1. 工业绿幕/绿色背景（H: 35~90）
+    2. 白色/浅色背景（高亮度、低饱和度）
+
+    逻辑：
+    - 将 PIL Image 转为 OpenCV 格式 (RGB → BGR)
+    - 转 HSV，分别生成绿色掩码和白色掩码
+    - 合并掩码后，按掩码将背景区域替换为中性灰
+    - 还原为 PIL Image (BGR → RGB) 返回
+
+    参数:
+        image: PIL Image (RGB, uint8)
+
+    返回:
+        处理后的 PIL Image (RGB, uint8)
+    """
+    # PIL (RGB) → OpenCV (BGR)
+    img_bgr = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+
+    # 转入 HSV 色彩空间
+    hsv = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2HSV)
+
+    # 生成掩码 1：绿色背景
+    mask_green = cv2.inRange(hsv, BG_GREEN_LOWER, BG_GREEN_UPPER)
+
+    # 生成掩码 2：白色/浅色背景
+    mask_white = cv2.inRange(hsv, BG_WHITE_LOWER, BG_WHITE_UPPER)
+
+    # 合并掩码（任意一种背景都替换）
+    mask_combined = cv2.bitwise_or(mask_green, mask_white)
+
+    # 形态学处理：消除噪点（小面积背景噪点填平）
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))
+    mask_combined = cv2.morphologyEx(mask_combined, cv2.MORPH_CLOSE, kernel)
+    mask_combined = cv2.morphologyEx(mask_combined, cv2.MORPH_OPEN, kernel)
+
+    # 背景替换：将掩码区域填充为中性灰
+    # 其中 mask_combined=255 的区域为背景，替换为 NEUTRAL_GRAY_BGR
+    img_bgr_no_bg = img_bgr.copy()
+    img_bgr_no_bg[mask_combined > 0] = NEUTRAL_GRAY_BGR
+
+    # OpenCV (BGR) → PIL (RGB)
+    result = Image.fromarray(cv2.cvtColor(img_bgr_no_bg, cv2.COLOR_BGR2RGB))
+
+    return result
+
+
+def _letterbox_image(image: Image.Image, size: int = 224) -> Image.Image:
+    """
+    Letterbox 预处理：等比例缩放 + 灰色填充，保持内容不变形
+
+    - 将原图最长边缩放到 224
+    - 短边按相同比例缩放
+    - 不足部分用 RGB(128,128,128) 灰色填充至 224x224
+
+    参数:
+        image: PIL Image 对象
+        size: 目标尺寸，默认 224
+
+    返回:
+        224x224 PIL Image
     """
     w, h = image.size
 
-    # 计算缩放后的目标尺寸
-    if w < h:
-        new_w = INPUT_SIZE
-        new_h = int(h * INPUT_SIZE / w)
-    else:
-        new_h = INPUT_SIZE
-        new_w = int(w * INPUT_SIZE / h)
+    # 计算缩放比例，使最长边等于 size
+    scale = size / max(w, h)
+    new_w = int(w * scale)
+    new_h = int(h * scale)
 
-    # 缩放
-    image = image.resize((new_w, new_h), Image.BILINEAR)
+    # 等比例缩放
+    resized = image.resize((new_w, new_h), Image.LANCZOS)
 
-    # 中心裁剪
-    left = (new_w - INPUT_SIZE) // 2
-    top = (new_h - INPUT_SIZE) // 2
-    right = left + INPUT_SIZE
-    bottom = top + INPUT_SIZE
+    # 创建灰色画布
+    canvas = Image.new('RGB', (size, size), (128, 128, 128))
 
-    return image.crop((left, top, right, bottom))
+    # 将缩放后的图片粘贴到画布正中央
+    paste_x = (size - new_w) // 2
+    paste_y = (size - new_h) // 2
+    canvas.paste(resized, (paste_x, paste_y))
+
+    return canvas
 
 
 def _normalize(image_np: np.ndarray) -> np.ndarray:
@@ -111,8 +194,12 @@ def get_image_embedding(image_path: str) -> list:
         load_clip_model()
 
     # 1. 图片预处理
+    #    Step 1: 背景去除（HSV 色彩空间，绿色/白色背景 → 中性灰替换）
     image = Image.open(image_path).convert('RGB')
-    image = _center_crop_and_resize(image)
+    image = _remove_background(image)
+
+    #    Step 2: Letterbox 等比例缩放（保持内容不变形）
+    image = _letterbox_image(image, INPUT_SIZE)
     input_data = _normalize(np.array(image))
     input_data = np.expand_dims(input_data, axis=0)  # [1, 3, 224, 224]
 

inventory-backend/requirements.txt

@@ -10,6 +10,8 @@ flask-cors==4.0.0
 redis==5.0.1
 # 图片处理核心库
 Pillow>=10.0.0
+# OpenCV（背景去除、HSV色彩空间抠图）
+opencv-python-headless>=4.8.0
 # ONNX 模型本地 CPU 推理
 onnxruntime>=1.16.0
 # 数值计算（ONNX 推理依赖）