931 lines
43 KiB
Python
931 lines
43 KiB
Python
import logging
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import threading
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import time
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import requests
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from minio import Minio
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from app.core.config import settings
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from app.service.design_fast.item import BodyItem, TopItem, BottomItem, OthersItem, TopMergeItem, BottomMergeItem, OthersMergeItem
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from app.service.design_fast.utils.organize import organize_body, organize_clothing, organize_others
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from app.service.design_fast.utils.progress import final_progress, update_progress
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from app.service.design_fast.utils.synthesis_item import synthesis, synthesis_single, update_base_size_priority, merge
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from app.service.utils.decorator import RunTime
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id_lock = threading.Lock()
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logger = logging.getLogger()
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minio_client = Minio(settings.MINIO_URL, access_key=settings.MINIO_ACCESS, secret_key=settings.MINIO_SECRET, secure=settings.MINIO_SECURE)
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def process_item(item, basic, design_type):
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# 1. 定义映射配置
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# key 为 item_type 的小写，value 为对应的处理类
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DESIGN_MAP = {
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"body": BodyItem,
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"blouse": TopItem,
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"outwear": TopItem,
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"dress": TopItem,
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"tops": TopItem,
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"skirt": BottomItem,
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"trousers": BottomItem,
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"bottoms": BottomItem,
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"others": OthersItem,
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}
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MERGE_MAP = {
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"body_merge": BodyItem,
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"blouse_merge": TopMergeItem,
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"outwear_merge": TopMergeItem,
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"dress_merge": TopMergeItem,
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"tops_merge": TopMergeItem,
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"skirt_merge": BottomMergeItem,
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"trousers_merge": BottomMergeItem,
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"bottoms_merge": BottomMergeItem,
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"others_merge": OthersMergeItem,
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}
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# 2. 根据 design_type 选择映射表
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mapping = MERGE_MAP if design_type == "merge" else DESIGN_MAP
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if design_type == "merge":
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item_type_key = f"{item['type'].lower()}_merge"
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elif design_type == "default":
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item_type_key = item["type"].lower()
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else:
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item_type_key = item["type"].lower()
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handler_class = mapping.get(item_type_key)
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if not handler_class:
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raise NotImplementedError(f"Item type {item['type']} not implemented for design_type={design_type}")
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# 4. 统一实例化并执行
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# 注意：这里假设所有 Item 类构造函数签名一致
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server = handler_class(data=item, basic=basic, minio_client=minio_client)
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item_data = server.process()
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return item_data
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def process_layer(item, layers):
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# item处理结束后 对图层数据组装
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if item["name"] == "mannequin":
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body_layer = organize_body(item)
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layers.append(body_layer)
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return item["body_image"].size
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elif item["name"] in ["others", "others_merge"]:
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front_layer, back_layer = organize_others(item)
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layers.append(front_layer)
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layers.append(back_layer)
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return None
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else:
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front_layer, back_layer = organize_clothing(item)
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layers.append(front_layer)
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layers.append(back_layer)
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return None
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@RunTime
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def design_generate(request_data):
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objects_data = request_data.dict()["objects"]
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process_id = request_data.dict()["process_id"]
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object_response = {}
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threads = []
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active_threads = 0
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lock = threading.Lock()
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total = len(objects_data)
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def process_object(step, object):
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nonlocal active_threads
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basic = object["basic"]
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items_response = {"layers": [], "objectSign": object["objectSign"] if "objectSign" in object.keys() else ""}
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design_type = basic.get("design_type", "default")
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if basic["single_overall"] == "overall":
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item_results = []
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for item in object["items"]:
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item_results.append(process_item(item, basic, design_type))
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layers = []
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for item in item_results:
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process_layer(item, layers)
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layers = sorted(layers, key=lambda s: s.get("priority", float("inf")))
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layers, new_size = update_base_size_priority(layers)
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# pattern_overall_image_url 、 pattern_print_image_url
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for lay in layers:
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items_response["layers"].append(
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{
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"image_category": "body" if lay["name"] == "mannequin" else lay["name"],
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"position": lay["position"],
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"priority": lay.get("priority", None),
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"resize_scale": lay["resize_scale"] if "resize_scale" in lay.keys() else None,
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"image_size": lay["image"] if lay["image"] is None else lay["image"].size,
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"gradient_string": lay["gradient_string"] if "gradient_string" in lay.keys() else "",
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"mask_url": lay["mask_url"],
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"image_url": lay["image_url"] if "image_url" in lay.keys() else None,
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"pattern_overall_image_url": (
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lay["pattern_overall_image_url"] if "pattern_overall_image_url" in lay.keys() else None
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),
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"pattern_print_image_url": lay["pattern_print_image_url"] if "pattern_print_image_url" in lay.keys() else None,
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"transpose": lay.get("transpose", None),
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"rotate": lay.get("rotate", None),
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# 'back_perspective_url': lay['back_perspective_url'] if 'back_perspective_url' in lay.keys() else None,
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}
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)
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if basic.get("design_type") == "default":
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items_response["synthesis_url"] = synthesis(layers, new_size, basic)
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elif basic.get("design_type") == "merge":
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items_response["synthesis_url"] = merge(layers, new_size, basic)
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else:
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items_response["synthesis_url"] = synthesis(layers, new_size, basic)
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else:
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item_result = process_item(object["items"][0], basic, design_type)
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items_response["layers"].append(
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{
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"image_category": f"{item_result['name']}_front",
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"image_size": item_result["back_image"].size if item_result["back_image"] else None,
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"position": None,
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"priority": 0,
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"image_url": item_result["front_image_url"],
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"mask_url": item_result["mask_url"],
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"gradient_string": item_result["gradient_string"] if "gradient_string" in item_result.keys() else "",
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"pattern_overall_image_url": (
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item_result["pattern_overall_image_url"] if "pattern_overall_image_url" in item_result.keys() else None
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),
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"pattern_print_image_url": (
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item_result["pattern_print_image_url"] if "pattern_print_image_url" in item_result.keys() else None
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),
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}
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)
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items_response["layers"].append(
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{
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"image_category": f"{item_result['name']}_back",
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"image_size": item_result["front_image"].size if item_result["front_image"] else None,
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"position": None,
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"priority": 0,
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"image_url": item_result["back_image_url"],
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"mask_url": item_result["mask_url"],
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"gradient_string": item_result["gradient_string"] if "gradient_string" in item_result.keys() else "",
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"pattern_overall_image_url": (
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item_result["pattern_overall_image_url"] if "pattern_overall_image_url" in item_result.keys() else None
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),
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"pattern_print_image_url": (
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item_result["pattern_print_image_url"] if "pattern_print_image_url" in item_result.keys() else None
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),
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}
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)
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items_response["synthesis_url"] = synthesis_single(item_result["front_image"], item_result["back_image"])
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update_progress(process_id, total)
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with lock:
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object_response[step] = items_response
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active_threads -= 1
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for step, object in enumerate(objects_data):
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t = threading.Thread(target=process_object, args=(step, object))
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threads.append(t)
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t.start()
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with lock:
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active_threads += 1
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for t in threads:
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t.join()
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final_progress(process_id)
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return object_response
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@RunTime
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def design_generate_v2(request_data):
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objects_data = request_data.dict()["objects"]
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callback_url = request_data.callback_url
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request_id = request_data.requestId
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threads = []
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def process_object(object, callback_url):
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basic = object["basic"]
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design_type = basic.get("design_type", "default")
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items_response = {
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"layers": [],
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"objectSign": object["objectSign"] if "objectSign" in object.keys() else "",
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"requestId": request_id,
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}
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if basic["single_overall"] == "overall":
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item_results = []
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for item in object["items"]:
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item_results.append(process_item(item, basic, design_type))
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layers = []
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for item in item_results:
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process_layer(item, layers)
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layers = sorted(layers, key=lambda s: s.get("priority", float("inf")))
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layers, new_size = update_base_size_priority(layers)
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for lay in layers:
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items_response["layers"].append(
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{
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"image_category": "body" if lay["name"] == "mannequin" else lay["name"],
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"position": lay["position"],
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"priority": lay.get("priority", None),
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"resize_scale": lay["resize_scale"] if "resize_scale" in lay.keys() else None,
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"image_size": lay["image"] if lay["image"] is None else lay["image"].size,
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"gradient_string": lay["gradient_string"] if "gradient_string" in lay.keys() else "",
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"mask_url": lay["mask_url"],
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"image_url": lay["image_url"] if "image_url" in lay.keys() else None,
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"pattern_overall_image_url": (
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lay["pattern_overall_image_url"] if "pattern_overall_image_url" in lay.keys() else None
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),
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"pattern_print_image_url": lay["pattern_print_image_url"] if "pattern_print_image_url" in lay.keys() else None,
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# 'back_perspective_url': lay['back_perspective_url'] if 'back_perspective_url' in lay.keys() else None,
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}
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)
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items_response["synthesis_url"] = synthesis(layers, new_size, basic)
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else:
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item_result = process_item(object["items"][0], basic, design_type)
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items_response["layers"].append(
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{
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"image_category": f"{item_result['name']}_front",
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"image_size": item_result["back_image"].size if item_result["back_image"] else None,
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"position": None,
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"priority": 0,
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"image_url": item_result["front_image_url"],
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"mask_url": item_result["mask_url"],
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"gradient_string": item_result["gradient_string"] if "gradient_string" in item_result.keys() else "",
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"pattern_overall_image_url": (
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item_result["pattern_overall_image_url"] if "pattern_overall_image_url" in item_result.keys() else None
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),
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"pattern_print_image_url": (
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item_result["pattern_print_image_url"] if "pattern_print_image_url" in item_result.keys() else None
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),
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}
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)
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items_response["layers"].append(
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{
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"image_category": f"{item_result['name']}_back",
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"image_size": item_result["front_image"].size if item_result["front_image"] else None,
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"position": None,
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"priority": 0,
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"image_url": item_result["back_image_url"],
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"mask_url": item_result["mask_url"],
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"gradient_string": item_result["gradient_string"] if "gradient_string" in item_result.keys() else "",
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"pattern_overall_image_url": (
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item_result["pattern_overall_image_url"] if "pattern_overall_image_url" in item_result.keys() else None
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),
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"pattern_print_image_url": (
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item_result["pattern_print_image_url"] if "pattern_print_image_url" in item_result.keys() else None
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),
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}
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)
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items_response["synthesis_url"] = synthesis_single(item_result["front_image"], item_result["back_image"])
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# 发送结果给java端
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url = callback_url
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logger.info(f"java 回调 -> {url}")
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headers = {
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"Accept": "*/*",
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"Accept-Encoding": "gzip, deflate, br",
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"User-Agent": "PostmanRuntime-ApipostRuntime/1.1.0",
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"Connection": "keep-alive",
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"Content-Type": "application/json",
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}
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# logger.info(items_response)
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response = post_request(url, json_data=items_response, headers=headers)
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if response:
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# 打印结果
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logger.info(response.text)
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t.start()
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# 等待所有线程完成，释放局部变量（图片等大对象）
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for t in threads:
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t.join()
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def post_request(url, data=None, json_data=None, headers=None, auth=None, timeout=5):
|
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"""
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发送POST请求的封装函数
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:param url: 接口的URL地址
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:param data: 要发送的数据（字典形式，用于表单数据等，会自动编码）
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:param json_data: 要发送的JSON数据（字典形式，会自动转换为JSON字符串）
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:param headers: 请求头字典
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: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
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:return: 返回接口的响应对象
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"""
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try:
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response = requests.post(url, data=data, json=json_data, headers=headers, auth=auth, timeout=timeout)
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response.raise_for_status() # 如果请求失败，抛出异常
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||
return response
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||
except requests.RequestException as e:
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||
print(f"POST请求出错: {e}")
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||
return None
|
||
|
||
|
||
if __name__ == "__main__":
|
||
object_data = {
|
||
"objects": [
|
||
{
|
||
"basic": {
|
||
"body_point_test": {
|
||
"waistband_right": [203, 249],
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"hand_point_right": [229, 343],
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||
"waistband_left": [119, 248],
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"hand_point_left": [97, 343],
|
||
"shoulder_left": [108, 107],
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||
"shoulder_right": [212, 107],
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||
},
|
||
"layer_order": False,
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||
"scale_bag": 0.7,
|
||
"scale_earrings": 0.16,
|
||
"self_template": True,
|
||
"single_overall": "overall",
|
||
"switch_category": "",
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||
},
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||
"items": [
|
||
{
|
||
"color": "28 26 26",
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||
"icon": "none",
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||
"image_id": 98419,
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||
"offset": [1, 1],
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"path": "aida-sys-image/images/female/dress/0825000526.jpg",
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||
"print": {
|
||
"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []},
|
||
"overall": {
|
||
"location": [[0.0, 0.0]],
|
||
"print_angle_list": [0.0, 0.0],
|
||
"print_path_list": [],
|
||
"print_scale_list": [0.0, 0.0],
|
||
},
|
||
"single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []},
|
||
},
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Dress",
|
||
},
|
||
{
|
||
"body_path": "aida-sys-image/models/female/2e4815b9-1191-419d-94ed-5771239ca4a5.png",
|
||
"image_id": 67277,
|
||
"offset": [1, 1],
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Body",
|
||
},
|
||
],
|
||
},
|
||
{
|
||
"basic": {
|
||
"body_point_test": {
|
||
"waistband_right": [203, 249],
|
||
"hand_point_right": [229, 343],
|
||
"waistband_left": [119, 248],
|
||
"hand_point_left": [97, 343],
|
||
"shoulder_left": [108, 107],
|
||
"shoulder_right": [212, 107],
|
||
},
|
||
"layer_order": False,
|
||
"scale_bag": 0.7,
|
||
"scale_earrings": 0.16,
|
||
"self_template": True,
|
||
"single_overall": "overall",
|
||
"switch_category": "",
|
||
},
|
||
"items": [
|
||
{
|
||
"color": "28 26 26",
|
||
"icon": "none",
|
||
"image_id": 98420,
|
||
"offset": [1, 1],
|
||
"path": "aida-sys-image/images/female/skirt/903000127.jpg",
|
||
"print": {
|
||
"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []},
|
||
"overall": {
|
||
"location": [[0.0, 0.0]],
|
||
"print_angle_list": [0.0, 0.0],
|
||
"print_path_list": [],
|
||
"print_scale_list": [0.0, 0.0],
|
||
},
|
||
"single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []},
|
||
},
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Skirt",
|
||
},
|
||
{
|
||
"color": "28 26 26",
|
||
"icon": "none",
|
||
"image_id": 69140,
|
||
"offset": [1, 1],
|
||
"path": "aida-sys-image/images/female/blouse/0902001100.jpg",
|
||
"print": {
|
||
"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []},
|
||
"overall": {
|
||
"location": [[0.0, 0.0]],
|
||
"print_angle_list": [0.0, 0.0],
|
||
"print_path_list": [],
|
||
"print_scale_list": [0.0, 0.0],
|
||
},
|
||
"single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []},
|
||
},
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Blouse",
|
||
},
|
||
{
|
||
"color": "28 26 26",
|
||
"icon": "none",
|
||
"image_id": 81604,
|
||
"offset": [1, 1],
|
||
"path": "aida-sys-image/images/female/outwear/outwear_p5_729.jpg",
|
||
"print": {
|
||
"element": {"element_angle_list": [], "element_path_list": [], "element_scale_list": [], "location": []},
|
||
"overall": {
|
||
"location": [[0.0, 0.0]],
|
||
"print_angle_list": [0.0, 0.0],
|
||
"print_path_list": [],
|
||
"print_scale_list": [0.0, 0.0],
|
||
},
|
||
"single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []},
|
||
},
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Outwear",
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|
||
"location": [[0.0, 0.0]],
|
||
"print_angle_list": [0.0, 0.0],
|
||
"print_path_list": [],
|
||
"print_scale_list": [0.0, 0.0],
|
||
},
|
||
"single": {"location": [], "print_angle_list": [], "print_path_list": [], "print_scale_list": []},
|
||
},
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Trousers",
|
||
},
|
||
{
|
||
"body_path": "aida-sys-image/models/female/2e4815b9-1191-419d-94ed-5771239ca4a5.png",
|
||
"image_id": 67277,
|
||
"offset": [1, 1],
|
||
"resize_scale": [1.0, 1.0],
|
||
"type": "Body",
|
||
},
|
||
],
|
||
},
|
||
],
|
||
"process_id": "123",
|
||
}
|
||
start_time = time.time()
|
||
X = design_generate(object_data)
|
||
print(time.time() - start_time)
|
||
print(X)
|