Merge branch 'refs/heads/develop'

# Conflicts:
#	app/api/api_query_image.py
#	app/service/search_image_with_text/service.py

.dockerignore

@@ -0,0 +1,2 @@
+seg_cache
+test

app/api/api_design.py

@@ -2,13 +2,13 @@ import json
 import logging
 import os
 
-from fastapi import APIRouter, HTTPException, UploadFile, File, Form
+from fastapi import APIRouter, HTTPException, UploadFile, File, Form, BackgroundTasks
 
 from app.schemas.design import DesignModel, DesignProgressModel, ModelProgressModel, DBGConfigModel
 from app.schemas.response_template import ResponseModel
 from app.service.design.model_process_service import model_transpose
 from app.service.design_batch.service import start_design_batch_generate
-from app.service.design_fast.design_generate import design_generate
+from app.service.design_fast.design_generate import design_generate, design_generate_v2
 from app.service.design_fast.utils.redis_utils import Redis
 
 router = APIRouter()
@@ -16,7 +16,7 @@ logger = logging.getLogger()
 
 
 @router.post("/design")
-def design(request_data: DesignModel):
+def design(request_data: DesignModel, background_tasks: BackgroundTasks):
     """
         创建一个具有以下参数的请求体:
         示例参数：
@@ -67,7 +67,6 @@ def design(request_data: DesignModel):
                                 0
                             ],
                             "path": "aida-sys-image/images/female/trousers/0825000630.jpg",
-                            "seg_mask_url": "test/result.png",
                             "print": {
                                 "element": {
                                     "element_angle_list": [],
@@ -104,7 +103,6 @@ def design(request_data: DesignModel):
                                 0
                             ],
                             "path": "aida-sys-image/images/female/blouse/0902003811.jpg",
-                            "seg_mask_url": "test/result.png",
                             "print": {
                                 "element": {
                                     "element_angle_list": [],
@@ -141,7 +139,6 @@ def design(request_data: DesignModel):
                                 0
                             ],
                             "path": "aida-sys-image/images/female/outwear/0825000410.jpg",
-                            "seg_mask_url": "test/result.png",
                             "print": {
                                 "element": {
                                     "element_angle_list": [],
@@ -167,6 +164,10 @@ def design(request_data: DesignModel):
                                 1.0,
                                 1.0
                             ],
+                            "transparent":{
+                                "mask_url":"test/transparent_test/transparent_mask.png",
+                                "scale":0.1
+                            },
                             "type": "Outwear"
                         },
                         {
@@ -195,6 +196,182 @@ def design(request_data: DesignModel):
     return ResponseModel(data=data)
 
 
+@router.post("/design_v2")
+async def design_v2(request_data: DesignModel, background_tasks: BackgroundTasks):
+    """
+        创建一个具有以下参数的请求体:
+        示例参数：
+        {
+            "objects": [
+                {
+                    "basic": {
+                        "body_point_test": {
+                            "waistband_right": [
+                                200,
+                                241
+                            ],
+                            "hand_point_right": [
+                                223,
+                                297
+                            ],
+                            "waistband_left": [
+                                112,
+                                241
+                            ],
+                            "hand_point_left": [
+                                92,
+                                305
+                            ],
+                            "shoulder_left": [
+                                99,
+                                116
+                            ],
+                            "shoulder_right": [
+                                215,
+                                116
+                            ]
+                        },
+                        "layer_order": true,
+                        "scale_bag": 0.7,
+                        "scale_earrings": 0.16,
+                        "self_template": true,
+                        "single_overall": "overall",
+                        "switch_category": ""
+                    },
+                    "items": [
+                        {
+                            "businessId": 270372,
+                            "color": "30 28 28",
+                            "image_id": 69780,
+                            "offset": [
+                                0,
+                                0
+                            ],
+                            "path": "aida-sys-image/images/female/trousers/0825000630.jpg",
+                            "print": {
+                                "element": {
+                                    "element_angle_list": [],
+                                    "element_path_list": [],
+                                    "element_scale_list": [],
+                                    "location": []
+                                },
+                                "overall": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                },
+                                "single": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                }
+                            },
+                            "priority": 10,
+                            "resize_scale": [
+                                1.0,
+                                1.0
+                            ],
+                            "type": "Trousers"
+                        },
+                        {
+                            "businessId": 270373,
+                            "color": "30 28 28",
+                            "image_id": 98243,
+                            "offset": [
+                                0,
+                                0
+                            ],
+                            "path": "aida-sys-image/images/female/blouse/0902003811.jpg",
+                            "print": {
+                                "element": {
+                                    "element_angle_list": [],
+                                    "element_path_list": [],
+                                    "element_scale_list": [],
+                                    "location": []
+                                },
+                                "overall": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                },
+                                "single": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                }
+                            },
+                            "priority": 11,
+                            "resize_scale": [
+                                1.0,
+                                1.0
+                            ],
+                            "type": "Blouse"
+                        },
+                        {
+                            "businessId": 270374,
+                            "color": "172 68 68",
+                            "image_id": 98244,
+                            "offset": [
+                                0,
+                                0
+                            ],
+                            "path": "aida-sys-image/images/female/outwear/0825000410.jpg",
+                            "print": {
+                                "element": {
+                                    "element_angle_list": [],
+                                    "element_path_list": [],
+                                    "element_scale_list": [],
+                                    "location": []
+                                },
+                                "overall": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                },
+                                "single": {
+                                    "location": [],
+                                    "print_angle_list": [],
+                                    "print_path_list": [],
+                                    "print_scale_list": []
+                                }
+                            },
+                            "priority": 12,
+                            "resize_scale": [
+                                1.0,
+                                1.0
+                            ],
+                            "transparent":{
+                                "mask_url":"test/transparent_test/transparent_mask.png",
+                                "scale":0.1
+                            },
+                            "type": "Outwear"
+                        },
+                        {
+                            "body_path": "aida-sys-image/models/female/5bdfe7ca-64eb-44e4-b03d-8e517520c795.png",
+                            "image_id": 96090,
+                            "type": "Body"
+                        }
+                    ]
+                }
+            ],
+            "process_id": "83"
+        }
+    """
+    try:
+        # 异步
+        logger.info(f"generate_image request item is : @@@@@@:{json.dumps(request_data.dict())}")
+        background_tasks.add_task(design_generate_v2, request_data)
+    except Exception as e:
+        logger.warning(f"design Run Exception @@@@@@:{e}")
+        raise HTTPException(status_code=404, detail=str(e))
+    return ResponseModel()
+
+
 @router.post('/get_progress')
 def get_progress(request_data: DesignProgressModel):
     """

app/api/api_generate_image.py

@@ -26,6 +26,7 @@ def generate_image(request_item: GenerateImageModel, background_tasks: Backgroun
         - **mode**: 生成模式，img2img或者txt2img
         - **category**: 生成图片的类别，sketch print 等等
         - **gender**: 生成sketch专用，服装类别
+        - **version**: 使用模型版本 fast 或者 high
 
         示例参数：
         {

app/api/api_query_image.py

@@ -1,8 +1,7 @@
 import json
 import logging
-from http.client import HTTPException
 
-from fastapi import APIRouter
+from fastapi import APIRouter, HTTPException
 
 from app.schemas.query_image import QueryImageModel
 from app.schemas.response_template import ResponseModel

app/service/design_fast/design_generate.py

@@ -2,11 +2,12 @@ import logging
 import threading
 import time
 
+import requests
 from minio import Minio
 
 from app.core.config import *
-from app.service.design_fast.item import BodyItem, TopItem, BottomItem
+from app.service.design_fast.item import BodyItem, TopItem, BottomItem, AccessoriesItem
-from app.service.design_fast.utils.organize import organize_body, organize_clothing
+from app.service.design_fast.utils.organize import organize_body, organize_clothing, organize_accessories
 from app.service.design_fast.utils.progress import final_progress, update_progress
 from app.service.design_fast.utils.synthesis_item import synthesis, synthesis_single, update_base_size_priority
 from app.service.utils.decorator import RunTime
@@ -26,9 +27,14 @@ def process_item(item, basic):
     elif item['type'].lower() in ['blouse', 'outwear', 'dress', 'tops']:
         top_server = TopItem(data=item, basic=basic, minio_client=minio_client)
         item_data = top_server.process()
-    else:
+    elif item['type'].lower() in ['skirt', 'trousers', 'bottoms']:
         bottom_server = BottomItem(data=item, basic=basic, minio_client=minio_client)
         item_data = bottom_server.process()
+    elif item['type'].lower() in ['accessories']:
+        bottom_server = AccessoriesItem(data=item, basic=basic, minio_client=minio_client)
+        item_data = bottom_server.process()
+    else:
+        raise NotImplementedError(f"Item type {item['type']} not implemented")
     return item_data
 
 
@@ -38,6 +44,10 @@ def process_layer(item, layers):
         body_layer = organize_body(item)
         layers.append(body_layer)
         return item['body_image'].size
+    elif item['name'] == 'accessories':
+        front_layer, back_layer = organize_accessories(item)
+        layers.append(front_layer)
+        layers.append(back_layer)
     else:
         front_layer, back_layer = organize_clothing(item)
         layers.append(front_layer)
@@ -57,7 +67,7 @@ def design_generate(request_data):
     def process_object(step, object):
         nonlocal active_threads
         basic = object['basic']
-        items_response = {'layers': []}
+        items_response = {'layers': [], 'objectSign': object['objectSign'] if 'objectSign' in object.keys() else ""}
         if basic['single_overall'] == "overall":
             item_results = []
             for item in object['items']:
@@ -81,6 +91,7 @@ def design_generate(request_data):
                     'mask_url': lay['mask_url'],
                     'image_url': lay['image_url'] if 'image_url' in lay.keys() else None,
                     'pattern_image_url': lay['pattern_image_url'] if 'pattern_image_url' in lay.keys() else None,
+                    # 'back_perspective_url': lay['back_perspective_url'] if 'back_perspective_url' in lay.keys() else None,
                 })
             items_response['synthesis_url'] = synthesis(layers, new_size, basic)
         else:
@@ -125,6 +136,117 @@ def design_generate(request_data):
     return object_response
 
 
+@RunTime
+def design_generate_v2(request_data):
+    objects_data = request_data.dict()['objects']
+    threads = []
+
+    def process_object(step, object):
+        basic = object['basic']
+        items_response = {
+            'layers': [],
+            'objectSign': object['objectSign'] if 'objectSign' in object.keys() else "",
+            'requestId': object['requestId'] if 'requestId' in object.keys() else ""
+        }
+        if basic['single_overall'] == "overall":
+            item_results = []
+            for item in object['items']:
+                item_results.append(process_item(item, basic))
+            layers = []
+            body_size = None
+            for item in item_results:
+                body_size = process_layer(item, layers)
+            layers = sorted(layers, key=lambda s: s.get("priority", float('inf')))
+
+            layers, new_size = update_base_size_priority(layers, body_size)
+
+            for lay in layers:
+                items_response['layers'].append({
+                    'image_category': "body" if lay['name'] == 'mannequin' else lay['name'],
+                    'position': lay['position'],
+                    'priority': lay.get("priority", None),
+                    'resize_scale': lay['resize_scale'] if "resize_scale" in lay.keys() else None,
+                    'image_size': lay['image'] if lay['image'] is None else lay['image'].size,
+                    'gradient_string': lay['gradient_string'] if 'gradient_string' in lay.keys() else "",
+                    'mask_url': lay['mask_url'],
+                    'image_url': lay['image_url'] if 'image_url' in lay.keys() else None,
+                    'pattern_image_url': lay['pattern_image_url'] if 'pattern_image_url' in lay.keys() else None,
+                    # 'back_perspective_url': lay['back_perspective_url'] if 'back_perspective_url' in lay.keys() else None,
+                })
+            items_response['synthesis_url'] = synthesis(layers, new_size, basic)
+        else:
+            item_result = process_item(object['items'][0], basic)
+            items_response['layers'].append({
+                'image_category': f"{item_result['name']}_front",
+                'image_size': item_result['back_image'].size if item_result['back_image'] else None,
+                'position': None,
+                'priority': 0,
+                'image_url': item_result['front_image_url'],
+                'mask_url': item_result['mask_url'],
+                "gradient_string": item_result['gradient_string'] if 'gradient_string' in item_result.keys() else "",
+                'pattern_image_url': item_result['pattern_image_url'] if 'pattern_image_url' in item_result.keys() else None,
+            })
+            items_response['layers'].append({
+                'image_category': f"{item_result['name']}_back",
+                'image_size': item_result['front_image'].size if item_result['front_image'] else None,
+                'position': None,
+                'priority': 0,
+                'image_url': item_result['back_image_url'],
+                'mask_url': item_result['mask_url'],
+                "gradient_string": item_result['gradient_string'] if 'gradient_string' in item_result.keys() else "",
+                'pattern_image_url': item_result['pattern_image_url'] if 'pattern_image_url' in item_result.keys() else None,
+            })
+            items_response['synthesis_url'] = synthesis_single(item_result['front_image'], item_result['back_image'])
+
+        #  发送结果给java端
+        url = "https://3998-117-143-125-51.ngrok-free.app/api/third/party/receiveDesignResults"
+        headers = {
+            'Accept': "*/*",
+            'Accept-Encoding': "gzip, deflate, br",
+            'User-Agent': "PostmanRuntime-ApipostRuntime/1.1.0",
+            'Connection': "keep-alive",
+            'Content-Type': "application/json"
+        }
+        response = post_request(url, json_data=items_response, headers=headers)
+        if response:
+            # 打印结果
+            logger.info(response.text)
+            logger.info(items_response)
+
+    for step, object in enumerate(objects_data):
+        t = threading.Thread(target=process_object, args=(step, object))
+        threads.append(t)
+        t.start()
+
+
+def post_request(url, data=None, json_data=None, headers=None, auth=None, timeout=5):
+    """
+    发送POST请求的封装函数
+
+    :param url: 接口的URL地址
+    :param data: 要发送的数据（字典形式，用于表单数据等，会自动编码）
+    :param json_data: 要发送的JSON数据（字典形式，会自动转换为JSON字符串）
+    :param headers: 请求头字典
+    :param auth: 认证信息（如 ('username', 'password') 形式用于基本认证）
+    :param timeout: 超时时间，单位为秒
+    :return: 返回接口的响应对象
+    """
+    try:
+        response = requests.post(
+            url,
+            data=data,
+            json=json_data,
+            headers=headers,
+            auth=auth,
+            timeout=timeout
+        )
+        response.raise_for_status()  # 如果请求失败，抛出异常
+        return response
+    except requests.RequestException as e:
+        print(f"POST请求出错: {e}")
+        return None
+
+
 if __name__ == '__main__':
     object_data = {
         "objects": [

app/service/design_fast/item.py

@@ -9,6 +9,27 @@ class BaseItem:
         self.result.update(basic)
 
 
+class AccessoriesItem(BaseItem):
+    def __init__(self, data, basic, minio_client):
+        super().__init__(data, basic)
+        self.Accessories_pipeline = [
+            LoadImage(minio_client),
+            # KeyPoint(),
+            ContourDetection(),
+            # Segmentation(minio_client),
+            # BackPerspective(minio_client),
+            Color(minio_client),
+            PrintPainting(minio_client),
+            Scaling(),
+            Split(minio_client)
+        ]
+
+    def process(self):
+        for item in self.Accessories_pipeline:
+            self.result = item(self.result)
+        return self.result
+
+
 class TopItem(BaseItem):
     def __init__(self, data, basic, minio_client):
         super().__init__(data, basic)
@@ -16,6 +37,7 @@ class TopItem(BaseItem):
             LoadImage(minio_client),
             KeyPoint(),
             Segmentation(minio_client),
+            # BackPerspective(minio_client),
             Color(minio_client),
             PrintPainting(minio_client),
             Scaling(),
@@ -36,6 +58,7 @@ class BottomItem(BaseItem):
             KeyPoint(),
             ContourDetection(),
             # Segmentation(),
+            # BackPerspective(minio_client),
             Color(minio_client),
             PrintPainting(minio_client),
             Scaling(),

app/service/design_fast/pipeline/__init__.py

@@ -1,3 +1,4 @@
+from .back_perspective import BackPerspective
 from .color import Color
 from .contour_detection import ContourDetection
 from .keypoint import KeyPoint
@@ -13,6 +14,7 @@ __all__ = [
     'KeyPoint',
     'ContourDetection',
     'Segmentation',
+    'BackPerspective',
     'Color',
     'PrintPainting',
     'Scaling',

app/service/design_fast/pipeline/back_perspective.py

@@ -0,0 +1,79 @@
+import cv2
+import numpy as np
+
+from app.service.design_fast.utils.design_ensemble import get_seg_result
+from app.service.utils.new_oss_client import oss_upload_image
+
+
+class BackPerspective:
+    def __init__(self, minio_client):
+        self.minio_client = minio_client
+
+    def __call__(self, result):
+
+        # 如果sketch为系统图 查看是否有对应的 背后视角图
+        if result['path'].split('/')[0] == 'aida-sys-image':
+            file_path = result['path'].replace("images", 'images_back', 1)
+            if self.is_file_exists(bucket_name='aida-sys-image', file_name=file_path[file_path.find('/') + 1:]):
+                result['back_perspective_url'] = file_path
+                return result
+            else:
+                seg_result = get_seg_result("1", result['image'])[0]
+        elif result['name'] in ['blouse', 'outwear', 'dress', 'tops']:
+            seg_result = result['seg_result']
+        else:
+            seg_result = get_seg_result("1", result['image'])[0]
+
+        m = self.thicken_contours_and_display(seg_result, thickness=10, color=(0, 0, 0))
+        back_sketch = result['image'].copy()
+        back_sketch[m > 100] = 255
+        # 上传背后视角图
+        _, img_encoded = cv2.imencode(".jpg", back_sketch)
+
+        resp = oss_upload_image(self.minio_client, bucket='test', object_name=result['path'], image_bytes=img_encoded.tobytes())
+        result['back_perspective_url'] = f"{resp.bucket_name}/{resp.object_name}"
+        return result
+
+    def thicken_contours_and_display(self, mask, thickness=10, color=(0, 0, 0)):
+        mask = mask.astype(np.uint8) * 255
+        # 查找轮廓
+        contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        # 创建一个彩色副本用于绘制轮廓
+        mask_color = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
+
+        def thicken_contour_inward(contour, thick):
+            # 创建一个空白的黑色图像与原始掩码大小相同
+            blank = np.zeros_like(mask)
+            # 在空白图像上绘制白色的轮廓
+            cv2.drawContours(blank, [contour], -1, 255, thickness=thick)
+            # 找到轮廓的中心（可以用重心等方法近似）
+            M = cv2.moments(contour)
+            cx = int(M['m10'] / M['m00'])
+            cy = int(M['m01'] / M['m00'])
+            # 进行距离变换，离中心越近的值越小
+            dist_transform = cv2.distanceTransform(255 - blank, cv2.DIST_L2, 5)
+            # 根据距离变换的值来决定是否保留像素，离中心近的像素更容易被保留
+            result = np.zeros_like(mask)
+            for i in range(dist_transform.shape[0]):
+                for j in range(dist_transform.shape[1]):
+                    if dist_transform[i, j] < thick:
+                        result[i, j] = 255
+            return result
+
+        for contour in contours:
+            thickened_contour = thicken_contour_inward(contour, thickness)
+            mask_color[thickened_contour > 0] = color
+
+        _, binary_result = cv2.threshold(mask_color, 127, 255, cv2.THRESH_BINARY)
+
+        # 转换为掩码形式
+        mask_result = cv2.cvtColor(binary_result, cv2.COLOR_BGR2GRAY)
+        return mask_result
+
+    def is_file_exists(self, bucket_name, file_name):
+        try:
+            self.minio_client.stat_object(bucket_name, file_name)
+            return True
+        except Exception:
+            return False

app/service/design_fast/pipeline/color.py

@@ -14,11 +14,18 @@ class Color:
 
     def __call__(self, result):
         dim_image_h, dim_image_w = result['image'].shape[0:2]
+        # 渐变色
         if "gradient" in result.keys() and result['gradient'] != "":
             bucket_name = result['gradient'].split('/')[0]
             object_name = result['gradient'][result['gradient'].find('/') + 1:]
             pattern = self.get_gradient(bucket_name=bucket_name, object_name=object_name)
             resize_pattern = cv2.resize(pattern, (dim_image_w, dim_image_h), interpolation=cv2.INTER_AREA)
+        # 无色
+        elif "color" not in result.keys() or result['color'] == "":
+            result['final_image'] = result['pattern_image'] = result['single_image'] = result['image']
+            result['alpha'] = 100 / 255.0
+            return result
+        # 正常颜色
         else:
             pattern = self.get_pattern(result['color'])
             resize_pattern = cv2.resize(pattern, (dim_image_w, dim_image_h), interpolation=cv2.INTER_AREA)

app/service/design_fast/pipeline/loading.py

@@ -74,6 +74,8 @@ class LoadImage:
             keypoint = 'head_point'
         elif name == 'earring':
             keypoint = 'ear_point'
+        elif name == 'accessories':
+            keypoint = "accessories"
         else:
             raise KeyError(f"{name} does not belong to item category list: blouse, outwear, dress, trousers, skirt, "
                            f"bag, shoes, hairstyle, earring.")

app/service/design_fast/pipeline/scale.py

@@ -46,4 +46,16 @@ class Scaling:
             result['scale'] = result['scale_bag']
         elif result['keypoint'] == 'ear_point':
             result['scale'] = result['scale_earrings']
+        elif result['keypoint'] == 'accessories':
+            # 由于没有识别配饰keypoint的模型  所以统一将配饰的两个关键点设定为 (0,0) (0,img.width)
+            # 模特的关键点设定为(0,0) (0,320/2) 距离比例简写为 160 / img.width
+            distance_clo = result['img_shape'][1]
+            distance_bdy = 320 / 2
+
+            if distance_clo == 0:
+                result['scale'] = 1
+            else:
+                result['scale'] = distance_bdy / distance_clo
+        else:
+            result['scale'] = 1
         return result

app/service/design_fast/pipeline/split.py

@@ -8,9 +8,10 @@ from cv2 import cvtColor, COLOR_BGR2RGBA
 
 from app.core.config import AIDA_CLOTHING
 from app.service.design_fast.utils.conversion_image import rgb_to_rgba
+from app.service.design_fast.utils.transparent import sketch_to_transparent
 from app.service.design_fast.utils.upload_image import upload_png_mask
 from app.service.utils.generate_uuid import generate_uuid
-from app.service.utils.new_oss_client import oss_upload_image
+from app.service.utils.new_oss_client import oss_upload_image, oss_get_image
 
 
 class Split(object):
@@ -20,7 +21,7 @@ class Split(object):
     def __call__(self, result):
         try:
 
-            if result['name'] in ('outwear', 'dress', 'blouse', 'skirt', 'trousers', 'tops', 'bottoms'):
+            if result['name'] in ('outwear', 'dress', 'blouse', 'skirt', 'trousers', 'tops', 'bottoms','accessories'):
                 front_mask = result['front_mask']
                 back_mask = result['back_mask']
                 rgba_image = rgb_to_rgba(result['final_image'], front_mask + back_mask)
@@ -30,6 +31,24 @@ class Split(object):
                 front_mask = cv2.resize(front_mask, new_size)
                 result_front_image[front_mask != 0] = rgba_image[front_mask != 0]
                 result_front_image_pil = Image.fromarray(cvtColor(result_front_image, COLOR_BGR2RGBA))
+                if 'transparent' in result.keys():
+                    #  用户自选区域transparent
+                    transparent = result['transparent']
+                    if transparent['mask_url'] is not None and transparent['mask_url'] != "":
+                        # 预处理用户自选区mask
+                        seg_mask = oss_get_image(oss_client=self.minio_client, bucket=transparent['mask_url'].split('/')[0], object_name=transparent['mask_url'][transparent['mask_url'].find('/') + 1:], data_type="cv2")
+                        seg_mask = cv2.resize(seg_mask, new_size, interpolation=cv2.INTER_NEAREST)
+                        # 转换颜色空间为 RGB（OpenCV 默认是 BGR）
+                        image_rgb = cv2.cvtColor(seg_mask, cv2.COLOR_BGR2RGB)
+
+                        r, g, b = cv2.split(image_rgb)
+                        blue_mask = b > r
+
+                        # 创建红色和绿色掩码
+                        transparent_mask = np.array(blue_mask, dtype=np.uint8) * 255
+                        result_front_image_pil = sketch_to_transparent(result_front_image_pil, transparent_mask, transparent["scale"])
+                    else:
+                        result_front_image_pil = sketch_to_transparent(result_front_image_pil, front_mask, transparent["scale"])
                 result['front_image'], result["front_image_url"], _ = upload_png_mask(self.minio_client, result_front_image_pil, f'{generate_uuid()}', mask=None)
 
                 height, width = front_mask.shape

app/service/design_fast/utils/design_ensemble.py

@@ -85,7 +85,7 @@ def seg_preprocess(img_path):
     if ori_shape != (img_scale_w, img_scale_h):
         # mmcv.imresize(img, img_scale_h, img_scale_w) # 老代码 引以为戒！哈哈哈~ h和w写反了
         img = cv2.resize(img, (img_scale_h, img_scale_w))
-    img = mmcv.imnormalize(img, mean=np.array([123.675, 116.28, 103.53]), std=np.array([58.395, 57.12, 57.375]), to_rgb=True)
+    # img = mmcv.imnormalize(img, mean=np.array([123.675, 116.28, 103.53]), std=np.array([58.395, 57.12, 57.375]), to_rgb=True)
     preprocessed_img = np.expand_dims(img.transpose(2, 0, 1), axis=0)
     return preprocessed_img, ori_shape
 

app/service/design_fast/utils/organize.py

@@ -33,8 +33,8 @@ def organize_clothing(layer):
                        mask=cv2.resize(layer['mask'], layer["front_image"].size),
                        gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
                        pattern_image_url=layer['pattern_image_url'],
-                       pattern_image=layer['pattern_image']
+                       pattern_image=layer['pattern_image'],
-
+                       # back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
                        )
     # 后片数据
     back_layer = dict(priority=-layer.get("priority", 0) if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_back', None),
@@ -50,6 +50,46 @@ def organize_clothing(layer):
                       mask=cv2.resize(layer['mask'], layer["front_image"].size),
                       gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
                       pattern_image_url=layer['pattern_image_url'],
+                      # back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
+                      )
+    return front_layer, back_layer
+
+
+def organize_accessories(layer):
+    # 起始坐标
+    start_point = (0, 0)
+    # 前片数据
+    front_layer = dict(priority=layer['priority'] if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_front', None),
+                       name=f'{layer["name"].lower()}_front',
+                       image=layer["front_image"],
+                       # mask_image=layer['front_mask_image'],
+                       image_url=layer['front_image_url'],
+                       mask_url=layer['mask_url'],
+                       sacle=layer['scale'],
+                       clothes_keypoint=(0, 0),
+                       position=start_point,
+                       resize_scale=layer["resize_scale"],
+                       mask=cv2.resize(layer['mask'], layer["front_image"].size),
+                       gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
+                       pattern_image_url=layer['pattern_image_url'],
+                       pattern_image=layer['pattern_image'],
+                       # back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
+                       )
+    # 后片数据
+    back_layer = dict(priority=-layer.get("priority", 0) if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_back', None),
+                      name=f'{layer["name"].lower()}_back',
+                      image=layer["back_image"],
+                      # mask_image=layer['back_mask_image'],
+                      image_url=layer['back_image_url'],
+                      mask_url=layer['mask_url'],
+                      sacle=layer['scale'],
+                      clothes_keypoint=(0, 0),
+                      position=start_point,
+                      resize_scale=layer["resize_scale"],
+                      mask=cv2.resize(layer['mask'], layer["front_image"].size),
+                      gradient_string=layer['gradient_string'] if 'gradient_string' in layer.keys() else "",
+                      pattern_image_url=layer['pattern_image_url'],
+                      # back_perspective_url=layer['back_perspective_url'] if 'back_perspective_url' in layer.keys() else ""
                       )
     return front_layer, back_layer
 

app/service/design_fast/utils/synthesis_item.py

@@ -79,9 +79,11 @@ def synthesis(data, size, basic_info):
         _, binary_body_mask = cv2.threshold(body_mask, 127, 255, cv2.THRESH_BINARY)
         top_outer_mask = np.array(binary_body_mask)
         bottom_outer_mask = np.array(binary_body_mask)
+        accessories_outer_mask = np.array(binary_body_mask)
 
         top = True
         bottom = True
+        accessories = True
         i = len(data)
         while i:
             i -= 1
@@ -109,10 +111,23 @@ def synthesis(data, size, basic_info):
                 background = np.zeros_like(top_outer_mask)
                 background[all_y_start:all_y_end, all_x_start:all_x_end] = sketch_mask[mask_y_start:mask_y_end, mask_x_start:mask_x_end]
                 bottom_outer_mask = background + bottom_outer_mask
+            elif accessories and data[i]['name'] in ['accessories_front']:
+                mask_shape = data[i]['mask'].shape
+                y_offset, x_offset = data[i]['adaptive_position']
+                # 初始化叠加区域的起始和结束位置
+                all_y_start, all_y_end, mask_y_start, mask_y_end = positioning(all_mask_shape=all_mask_shape[0], mask_shape=mask_shape[0], offset=y_offset)
+                all_x_start, all_x_end, mask_x_start, mask_x_end = positioning(all_mask_shape=all_mask_shape[1], mask_shape=mask_shape[1], offset=x_offset)
+                # 将叠加区域赋值为相应的像素值
+                _, sketch_mask = cv2.threshold(data[i]['mask'], 127, 255, cv2.THRESH_BINARY)
+                background = np.zeros_like(top_outer_mask)
+                background[all_y_start:all_y_end, all_x_start:all_x_end] = sketch_mask[mask_y_start:mask_y_end, mask_x_start:mask_x_end]
+                accessories_outer_mask = background + accessories_outer_mask
+                pass
             elif bottom is False and top is False:
                 break
 
         all_mask = cv2.bitwise_or(top_outer_mask, bottom_outer_mask)
+        all_mask = cv2.bitwise_or(all_mask, accessories_outer_mask)
 
         for layer in data:
             if layer['image'] is not None:

app/service/design_fast/utils/transparent.py

@@ -0,0 +1,26 @@
+from PIL import Image
+
+
+def sketch_to_transparent(image, mask, transparency):
+    # 打开原始图片
+    image = image.convert("RGBA")
+    # 打开mask图片，假设mask图片是灰度图，白色区域为要处理的区域，黑色区域为保留的区域
+    mask = Image.fromarray(mask)
+
+    # 根据透明度调整因子，将透明度转换为0-255之间的值
+    alpha_value = int((1 - transparency) * 255.0)
+
+    # 获取图片的像素数据
+    image_pixels = image.load()
+    mask_pixels = mask.load()
+
+    width, height = image.size
+
+    for y in range(height):
+        for x in range(width):
+            # 如果mask区域对应的像素为白色（值大于128，这里假设白色为要处理的区域，可根据实际情况调整）
+            if mask_pixels[x, y] > 128:
+                r, g, b, a = image_pixels[x, y]
+                image_pixels[x, y] = (r, g, b, alpha_value)
+
+    return image

app/service/search_image_with_text/service.py

@@ -6,6 +6,8 @@ from chromadb.config import Settings
 from chromadb.utils.embedding_functions.ollama_embedding_function import OllamaEmbeddingFunction
 from tqdm import tqdm
 
+from app.core.config import OLLAMA_URL
+
 # 读取 csv 文件
 # csv_file_path = r'D:/Files/csv/output/output.csv'
 # image_path = r'D:/images-clean'
@@ -17,7 +19,8 @@ client = chromadb.Client(Settings(is_persistent=True, persist_directory="/vector
 # client = chromadb.Client(Settings(is_persistent=True, persist_directory="./service/search_image_with_text/vector_db"))
 # client = chromadb.Client(Settings(is_persistent=True, persist_directory="D:/workspace/AiDLab/vector_db"))
 # 创建集合
-embedding_fn = OllamaEmbeddingFunction(url="http://10.1.1.240:11434/api/embeddings", model_name="mxbai-embed-large")
+# embedding_fn = OllamaEmbeddingFunction(url="http://localhost:11434/api/embeddings", model_name="mxbai-embed-large")
+embedding_fn = OllamaEmbeddingFunction(url=OLLAMA_URL, model_name="mxbai-embed-large")
 
 
 # def create_collection():
@@ -66,7 +69,7 @@ embedding_fn = OllamaEmbeddingFunction(url="http://10.1.1.240:11434/api/embeddin
 def query(gender, content):
     collection = client.get_collection("sub_sketches_description", embedding_function=embedding_fn)
     # 6. 查询相似内容
-    user_gender = gender  # 用户输入的性别
+    user_gender = gender.lower()  # 用户输入的性别
     user_content = content  # 用户输入的内容
 
     results = collection.query(

app/service/utils/new_oss_client.py

@@ -82,9 +82,10 @@ if __name__ == '__main__':
     # url = "aida-users/89/sketchboard/female/Dress/e6724ab7-8d3f-4677-abe0-c3e42ab7af85.jpeg"
     # 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/31/sketchboard/female/dress/6edcbf92-7da9-4809-a0a8-a4b4f06dec1e0628000041.jpg"
+    url = "aida-users/89/test/123-89.png"
+
     # url = "aida-collection-element/12148/Sketchboard/95ea577b-305b-4a62-b30a-39c0dd3ddb3f.png"
-    read_type = "cv2"
+    read_type = "2"
     if read_type == "cv2":
         img = oss_get_image(oss_client=minio_client, bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type)
         cv2.imshow("", img)