feat 测试批量上传图片

fix
2024-07-19 15:10:28 +08:00
parent b92b1f7d6e
commit ed908d0472
13 changed files with 160 additions and 48 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -120,6 +120,7 @@ dmypy.json

 #runtime produce
 test
+seg_cache
 logs
 seg_result/
 seg_result
--- a/app/api/api_design.py
+++ b/app/api/api_design.py
@@ -136,13 +136,16 @@ def design(request_data: DesignModel):
            "process_id": "89"
        }
    """
-    try:
    logger.info(f"design request item is : @@@@@@:{json.dumps(request_data.dict())}")
    data = generate(request_data=request_data)
    logger.info(f"design response @@@@@@:{json.dumps(data)}")
-    except Exception as e:
-        logger.warning(f"design Run Exception @@@@@@:{e}")
-        raise HTTPException(status_code=404, detail=str(e))
+    # try:
+    #     logger.info(f"design request item is : @@@@@@:{json.dumps(request_data.dict())}")
+    #     data = generate(request_data=request_data)
+    #     logger.info(f"design response @@@@@@:{json.dumps(data)}")
+    # except Exception as e:
+    #     logger.warning(f"design Run Exception @@@@@@:{e}")
+    #     raise HTTPException(status_code=404, detail=str(e))
    return ResponseModel(data=data)


--- a/app/core/config.py
+++ b/app/core/config.py
@@ -24,11 +24,11 @@ DEBUG = False
 if DEBUG:
    LOGS_PATH = "logs/"
    CATEGORY_PATH = "service/attribute/config/descriptor/category/category_dis.csv"
-    # FACE_CLASSIFIER = "service/generate_image/utils/haarcascade_frontalface_alt.xml"
+    SEG_CACHE_PATH = "../seg_cache/"
 else:
    LOGS_PATH = "app/logs/"
    CATEGORY_PATH = "app/service/attribute/config/descriptor/category/category_dis.csv"
-    # FACE_CLASSIFIER = 'app/service/generate_image/utils/haarcascade_frontalface_alt.xml'
+    SEG_CACHE_PATH = "/seg_cache/"

 # RABBITMQ_ENV = ""  # 生产环境
 RABBITMQ_ENV = "-dev"  # 开发环境
--- a/app/service/design/items/clothing.py
+++ b/app/service/design/items/clothing.py
@@ -37,7 +37,8 @@ class Clothing(object):
                           resize_scale=self.result["resize_scale"],
                           mask=cv2.resize(self.result['mask'], self.result["front_image"].size),
                           gradient_string=self.result['gradient_string'] if 'gradient_string' in self.result.keys() else "",
-                           pattern_image_url=self.result['pattern_image_url']
+                           pattern_image_url=self.result['pattern_image_url'],
+                           pattern_image=self.result['pattern_image']

                           )
        layer.insert(front_layer)
@@ -54,7 +55,7 @@ class Clothing(object):
                          resize_scale=self.result["resize_scale"],
                          mask=cv2.resize(self.result['mask'], self.result["front_image"].size),
                          gradient_string=self.result['gradient_string'] if 'gradient_string' in self.result.keys() else "",
-                          pattern_image_url=self.result['pattern_image_url']
+                          pattern_image_url=self.result['pattern_image_url'],
                          )
        layer.insert(back_layer)

--- a/app/service/design/items/pipelines/keypoints.py
+++ b/app/service/design/items/pipelines/keypoints.py
@@ -5,6 +5,7 @@ import numpy as np
 from pymilvus import MilvusClient

 from app.core.config import *
+from app.service.utils.decorator import RunTime, ClassCallRunTime
 from ..builder import PIPELINES
 from ...utils.design_ensemble import get_keypoint_result

@@ -27,7 +28,7 @@ class KeypointDetection(object):
    # self.client.close()
    # print(f"client close time : {time.time() - start_time}")

-    # @ RunTime
+    @ ClassCallRunTime
    def __call__(self, result):
        # logging.info("KeypointDetection run ")
        if result['name'] in ['blouse', 'skirt', 'dress', 'outwear', 'trousers', 'tops', 'bottoms']:  # 查询是否有数据 且类别相同 相同则直接读 不同则推理后更新
--- a/app/service/design/items/pipelines/loading.py
+++ b/app/service/design/items/pipelines/loading.py
@@ -1,5 +1,6 @@
 import cv2

+from app.service.utils.decorator import RunTime, ClassCallRunTime
 from app.service.utils.oss_client import oss_get_image
 from ..builder import PIPELINES

@@ -12,6 +13,7 @@ class LoadImageFromFile(object):
        self.print_dict = print_dict
        # self.minio_client = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)

+    @ClassCallRunTime
    def __call__(self, result):
        result['image'], result['pre_mask'] = self.read_image(self.path)
        result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)
--- a/app/service/design/items/pipelines/painting.py
+++ b/app/service/design/items/pipelines/painting.py
@@ -4,6 +4,7 @@ import cv2
 import numpy as np
 from PIL import Image

+from app.service.utils.decorator import RunTime, ClassCallRunTime
 from app.service.utils.oss_client import oss_get_image
 from ..builder import PIPELINES

@@ -13,7 +14,7 @@ class Painting(object):
    def __init__(self, painting_flag=True):
        self.painting_flag = painting_flag

-    # @ RunTime
+    @ClassCallRunTime
    def __call__(self, result):
        if result['name'] not in ['hairstyle', 'earring'] and self.painting_flag and result['color'] != 'none':
            dim_image_h, dim_image_w = result['image'].shape[0:2]
@@ -86,7 +87,7 @@ class PrintPainting(object):
    def __init__(self, print_flag=True):
        self.print_flag = print_flag

-    # @ RunTime
+    @ClassCallRunTime
    def __call__(self, result):
        single_print = result['print']['single']
        overall_print = result['print']['overall']
@@ -236,7 +237,6 @@ class PrintPainting(object):

                    print_background = cv2.cvtColor(np.array(source_image_pil), cv2.COLOR_RGBA2BGR)
                    mask_background = cv2.cvtColor(np.array(source_image_pil_mask), cv2.COLOR_RGBA2BGR)
-                    print(1)
                else:
                    mask = self.get_mask_inv(image)
                    mask = np.expand_dims(mask, axis=2)
--- a/app/service/design/items/pipelines/scale.py
+++ b/app/service/design/items/pipelines/scale.py
@@ -2,6 +2,7 @@ import math

 import cv2

+from app.service.utils.decorator import ClassCallRunTime
 from ..builder import PIPELINES


@@ -10,7 +11,7 @@ class Scaling(object):
    def __init__(self):
        pass

-    # @ RunTime
+    @ClassCallRunTime
    def __call__(self, result):
        if result['keypoint'] in ['waistband', 'shoulder', 'head_point']:
            # milvus_db_keypoint_cache
--- a/app/service/design/items/pipelines/segmentation.py
+++ b/app/service/design/items/pipelines/segmentation.py
@@ -1,3 +1,9 @@
+import os
+
+import numpy as np
+
+from app.core.config import SEG_CACHE_PATH
+from app.service.utils.decorator import ClassCallRunTime
 from ..builder import PIPELINES
 from ...utils.design_ensemble import get_seg_result

@@ -9,6 +15,32 @@ class Segmentation(object):
        self.device = device
        self.debug = debug

+    @ClassCallRunTime
    def __call__(self, result):
+        _, seg_result = self.load_seg_result(result["image_id"])
+        if not _:
            result['seg_result'] = get_seg_result(result["image_id"], result['image'])
+            self.save_seg_result(result['seg_result'][0], result['image_id'])
        return result
+
+    @staticmethod
+    def save_seg_result(seg_result, image_id):
+        file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
+        try:
+            np.save(file_path, seg_result)
+            print("保存成功", os.path.abspath(file_path))
+        except Exception as e:
+            print(f"保存失败: {e}")
+
+    @staticmethod
+    def load_seg_result(image_id):
+        file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
+        try:
+            seg_result = np.load(file_path)
+            return True, seg_result
+        except FileNotFoundError:
+            print("文件不存在")
+            return False, None
+        except Exception as e:
+            print(f"加载失败: {e}")
+            return False, None
--- a/app/service/design/items/pipelines/split.py
+++ b/app/service/design/items/pipelines/split.py
@@ -5,6 +5,7 @@ import numpy as np
 from PIL import Image
 from cv2 import cvtColor, COLOR_BGR2RGBA

+from app.service.utils.decorator import ClassCallRunTime
 from app.service.utils.generate_uuid import generate_uuid
 from ..builder import PIPELINES
 from ...utils.conversion_image import rgb_to_rgba
@@ -17,6 +18,7 @@ class Split(object):
    Split image into front and back layer according to the segmentation result
    """

+    @ClassCallRunTime
    # KNet
    def __call__(self, result):
        try:
@@ -66,7 +68,7 @@ class Split(object):
                # 创建中间图层
            result_pattern_image_rgba = rgb_to_rgba(result['pattern_image'], result['mask'])
            result_pattern_image_pil = Image.fromarray(cvtColor(result_pattern_image_rgba, COLOR_BGR2RGBA))
-            _, result['pattern_image_url'], _ = upload_png_mask(result_pattern_image_pil, f'{generate_uuid()}')
+            result['pattern'], result['pattern_image_url'], _ = upload_png_mask(result_pattern_image_pil, f'{generate_uuid()}')
            return result
        except Exception as e:
            logging.warning(f"split runtime exception : {e} image_id : {result['image_id']}")
--- a/app/service/design/service.py
+++ b/app/service/design/service.py
@@ -1,4 +1,8 @@
 import concurrent.futures
+import io
+
+import cv2
+from PIL import Image

 from app.core.config import PRIORITY_DICT
 from app.service.design.core.layer import Layer
@@ -6,6 +10,7 @@ from app.service.design.items import build_item
 from app.service.design.utils.redis_utils import Redis
 from app.service.design.utils.synthesis_item import synthesis, synthesis_single
 from app.service.utils.decorator import RunTime
+from app.service.utils.oss_client import oss_upload_image


 def process_item(item, layers):
@@ -43,6 +48,7 @@ def final_progress(process_id):
@RunTime
 def generate(request_data):
    return_response = {}
+    return_png_mask = []
    request_data = request_data.dict()
    assert "process_id" in request_data.keys(), "Need process_id parameters"

@@ -55,14 +61,15 @@ def generate(request_data):
        # 获取处理结果
        for future in concurrent.futures.as_completed(futures):
            obj = futures[future]
-
-            result = future.result()
-            return_response[obj] = result
+            return_response[obj] = future.result()[0]
+            return_png_mask.extend(future.result()[1])
    final_progress(process_id)
+    upload_results = process_images(return_png_mask)
    return return_response


 def process_object(cfg, process_id, total):
+    uploaded_images = []
    basic_info = cfg.get('basic')
    items_response = {
        'layers': []
@@ -83,6 +90,15 @@ def process_object(cfg, process_id, total):
            layers = sorted(layers.layer, key=lambda s: s.get("priority", float('inf')))
        else:
            layers = sorted(layers.layer, key=lambda x: PRIORITY_DICT.get(x['name'], float('inf')))
+        # 上传所有图片
+        for layer in layers:
+            if 'image' in layer.keys() and layer['image'] is not None:
+                uploaded_images.append({'image_obj': layer['image'], 'image_url': layer['image_url']})
+            if 'pattern_image' in layer.keys() and layer['pattern_image'] is not None:
+                uploaded_images.append({'image_obj': layer['pattern_image'], 'image_url': layer['pattern_image_url']})
+            if 'mask' in layer.keys() and layer['mask'] is not None and layer['mask_url'] is not None:
+                uploaded_images.append({'image_obj': layer['mask'], 'image_url': layer['mask_url']})
+
        # 合成
        items_response['synthesis_url'] = synthesis(layers, body_size)

@@ -131,4 +147,34 @@ def process_object(cfg, process_id, total):
                items_response['synthesis_url'] = synthesis_single(item.result['front_image'], item.result['back_image'])
                break
    update_progress(process_id, total)
-    return items_response
+    return items_response, uploaded_images
+
+
+@RunTime
+def process_images(images):
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        results = list(executor.map(upload_images, images))
+    # results = []
+    # for image in images:
+    #     results.append(upload_images(image))
+    return results
+
+
+@RunTime
+def upload_images(image_obj):
+    bucket_name = image_obj['image_url'].split("/", 1)[0]
+    object_name = image_obj['image_url'].split("/", 1)[1]
+    if isinstance(image_obj['image_obj'], Image.Image):
+        image_data = io.BytesIO()
+        image_obj['image_obj'].save(image_data, format='PNG')
+        image_data.seek(0)
+        image_bytes = image_data.read()
+        req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes)
+        return image_obj['image_url']
+    else:
+        mask_inverted = cv2.bitwise_not(image_obj['image_obj'])
+        # 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(bucket=bucket_name, object_name=object_name, image_bytes=cv2.imencode('.png', rgba_image)[1])
+        return image_obj['image_url']
--- a/app/service/design/utils/upload_image.py
+++ b/app/service/design/utils/upload_image.py
@@ -13,33 +13,43 @@ import logging
 import cv2

 from app.core.config import *
+from app.service.utils.decorator import RunTime
 from app.service.utils.oss_client import oss_upload_image


 # @RunTime
+# def upload_png_mask(front_image, object_name, mask=None):
+#     try:
+#         mask_url = None
+#         if mask is not None:
+#             mask_inverted = cv2.bitwise_not(mask)
+#             # 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]
+#             # image_bytes = io.BytesIO()
+#             # image_bytes.write(cv2.imencode('.png', rgba_image)[1].tobytes())
+#             # image_bytes.seek(0)
+#             # mask_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'mask/mask_{object_name}.png', image_bytes, len(image_bytes.getvalue()), content_type='image/png').object_name}"
+#             # oss upload ####################
+#             req = oss_upload_image(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()
+#         # image_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'image/image_{object_name}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
+#         req = oss_upload_image(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}")
+
+
+@RunTime
 def upload_png_mask(front_image, object_name, mask=None):
-    try:
    mask_url = None
    if mask is not None:
-            mask_inverted = cv2.bitwise_not(mask)
-            # 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]
-            # image_bytes = io.BytesIO()
-            # image_bytes.write(cv2.imencode('.png', rgba_image)[1].tobytes())
-            # image_bytes.seek(0)
-            # mask_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'mask/mask_{object_name}.png', image_bytes, len(image_bytes.getvalue()), content_type='image/png').object_name}"
-            # oss upload ####################
-            req = oss_upload_image(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()
-        # image_url = f"{AIDA_CLOTHING}/{minio_client.put_object('aida-clothing', f'image/image_{object_name}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"
-        req = oss_upload_image(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}")
--- a/app/service/utils/decorator.py
+++ b/app/service/utils/decorator.py
@@ -1,5 +1,5 @@
-import time
 import logging
+import time


 def RunTime(func):
@@ -12,3 +12,16 @@ def RunTime(func):
        return res

    return wrapper
+
+
+def ClassCallRunTime(func):
+    def wrapper(*args, **kwargs):
+        start_time = time.time()
+        result = func(*args, **kwargs)
+        end_time = time.time()
+        execution_time = end_time - start_time
+        class_name = args[0].__class__.__name__  # 获取类名
+        print(f"class name: {class_name} , run time is : {execution_time} s")
+        return result
+
+    return wrapper