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feat（新功能）: design batch 代码 更新

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fix（修复bug）:
docs（文档变更）:
refactor（重构）:
test(增加测试):
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zchengrong
2025-04-17 11:23:40 +08:00
parent 59095a4d6b
commit 88c9d6ef93
12 changed files with 399 additions and 71 deletions
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35
app/service/design_batch/pipeline/segmentation.py
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@@ -5,7 +5,8 @@ import cv2
import numpy as np
from app.core.config import SEG_CACHE_PATH
from app.service.design_batch.utils.design_ensemble import get_seg_result
from app.service.design_fast.utils.design_ensemble import get_seg_result
from app.service.utils.decorator import ClassCallRunTime
from app.service.utils.new_oss_client import oss_get_image
logger = logging.getLogger()
@@ -15,6 +16,7 @@ class Segmentation:
def __init__(self, minio_client):
self.minio_client = minio_client
@ClassCallRunTime
def __call__(self, result):
if "seg_mask_url" in result.keys() and result['seg_mask_url'] != "":
seg_mask = oss_get_image(oss_client=self.minio_client, bucket=result['seg_mask_url'].split('/')[0], object_name=result['seg_mask_url'][result['seg_mask_url'].find('/') + 1:], data_type="cv2")
@@ -31,24 +33,37 @@ class Segmentation:
result['back_mask'] = np.array(green_mask, dtype=np.uint8) * 255
result['mask'] = result['front_mask'] + result['back_mask']
else:
# 本地查询seg 缓存是否存在
_, seg_result = self.load_seg_result(result["image_id"])
result['seg_result'] = seg_result
if not _:
# preview 过模型 不缓存
if "preview_submit" in result.keys() and result['preview_submit'] == "preview":
# 推理获得seg 结果
seg_result = get_seg_result(result["image_id"], result['image'])[0]
seg_result = get_seg_result(result["image_id"], result['image'])
# submit 过模型 缓存
elif "preview_submit" in result.keys() and result['preview_submit'] == "submit":
# 推理获得seg 结果
seg_result = get_seg_result(result["image_id"], result['image'])
self.save_seg_result(seg_result, result['image_id'])
# null 正常流程 加载本地缓存 无缓存则过模型
else:
# 本地查询seg 缓存是否存在
_, seg_result = self.load_seg_result(result["image_id"])
# 判断缓存和实际图片size是否相同
if not _ or result["image"].shape[:2] != seg_result.shape:
# 推理获得seg 结果
seg_result = get_seg_result(result["image_id"], result['image'])
self.save_seg_result(seg_result, result['image_id'])
result['seg_result'] = seg_result
# 处理前片后片
temp_front = seg_result == 1.0
temp_front = seg_result == 1
result['front_mask'] = (255 * (temp_front + 0).astype(np.uint8))
temp_back = seg_result == 2.0
temp_back = seg_result == 2
result['back_mask'] = (255 * (temp_back + 0).astype(np.uint8))
result['mask'] = result['front_mask'] + result['back_mask']
return result
@staticmethod
def save_seg_result(seg_result, image_id):
file_path = f"seg_cache/{image_id}.npy"
file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
try:
np.save(file_path, seg_result)
logger.debug(f"保存成功 ：{os.path.abspath(file_path)}")
@@ -57,7 +72,7 @@ class Segmentation:
@staticmethod
def load_seg_result(image_id):
file_path = f"seg_cache/{image_id}.npy"
file_path = f"{SEG_CACHE_PATH}{image_id}.npy"
# logger.info(f"load seg file name is :{SEG_CACHE_PATH}{image_id}.npy")
try:
seg_result = np.load(file_path)