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Merge remote-tracking branch 'origin/develop' into develop

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# Conflicts:
#	app/service/design_fast/pipeline/split.py
#	app/service/utils/new_oss_client.py
This commit is contained in:
zhouchengrong
2025-02-06 18:37:46 +08:00
parent f4225bcb2c eed0ac13a1
commit 00b5045c64
3 changed files with 45 additions and 10 deletions
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15
app/service/design_fast/pipeline/loading.py
View File

@@ -1,9 +1,6 @@
import io
import logging
import cv2
import numpy as np
from PIL import Image
from app.service.utils.new_oss_client import oss_get_image
@@ -38,6 +35,18 @@ class LoadImage:
def __call__(self, result):
result['image'], result['pre_mask'] = self.read_image(result['path'])
# 判断是否resize sketch 保留ori image 用于模型输入
result['ori_image'] = result['image']
if result['resize_scale'][0] != 0 and result['resize_scale'][1] != 0:
height, width = result['image'].shape[:2]
# 计算新的宽度和高度
new_width = int(width * result['resize_scale'][0])
new_height = int(height * result['resize_scale'][1])
# 使用cv2.resize()函数进行缩放
result['image'] = cv2.resize(result['image'], (new_width, new_height))
if result['pre_mask'] is not None:
result['pre_mask'] = cv2.resize(result['pre_mask'], (new_width, new_height))
result['gray'] = cv2.cvtColor(result['image'], cv2.COLOR_BGR2GRAY)
result['keypoint'] = self.get_keypoint(result['name'])
result['img_shape'] = result['image'].shape

7
app/service/design_fast/pipeline/print_painting.py
View File

@@ -460,8 +460,11 @@ class PrintPainting:
angle: 旋转的角度
crop: 是否需要进行裁剪，布尔向量
"""
if not isinstance(crop, bool):
raise ValueError("The 'crop' parameter must be a boolean.")
crop_image = lambda img, x0, y0, w, h: img[y0:y0 + h, x0:x0 + w]
w, h = img.shape[:2]
h, w = img.shape[:2]
# 旋转角度的周期是360°
angle %= 360
# 计算仿射变换矩阵
@@ -473,7 +476,7 @@ class PrintPainting:
if crop:
# 裁剪角度的等效周期是180°
angle_crop = angle % 180
if angle > 90:
if angle_crop > 90:
angle_crop = 180 - angle_crop
# 转化角度为弧度
theta = angle_crop * np.pi / 180

33
app/service/design_fast/pipeline/segmentation.py
View File

@@ -36,12 +36,27 @@ class Segmentation:
# 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'])
seg_result = get_seg_result(result["image_id"], result['ori_image'])
if result['resize_scale'][0] != 0 and result['resize_scale'][1] != 0:
height, width = seg_result.shape[:2]
# 计算新的宽度和高度
new_width = int(width * result['resize_scale'][0])
new_height = int(height * result['resize_scale'][1])
# 使用cv2.resize()函数进行缩放
seg_result = cv2.resize(seg_result, (new_width, new_height))
# 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'])
seg_result = get_seg_result(result["image_id"], result['ori_image'])
seg_result_save = seg_result
if result['resize_scale'][0] != 0 and result['resize_scale'][1] != 0:
height, width = seg_result.shape[:2]
# 计算新的宽度和高度
new_width = int(width * result['resize_scale'][0])
new_height = int(height * result['resize_scale'][1])
# 使用cv2.resize()函数进行缩放
seg_result = cv2.resize(seg_result, (new_width, new_height))
self.save_seg_result(seg_result_save, 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
@@ -49,8 +64,16 @@ class Segmentation:
# 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'])
seg_result = get_seg_result(result["image_id"], result['ori_image'])
seg_result_save = seg_result
if result['resize_scale'][0] != 0 and result['resize_scale'][1] != 0:
height, width = seg_result.shape[:2]
# 计算新的宽度和高度
new_width = int(width * result['resize_scale'][0])
new_height = int(height * result['resize_scale'][1])
# 使用cv2.resize()函数进行缩放
seg_result = cv2.resize(seg_result, (new_width, new_height))
self.save_seg_result(seg_result_save, result['image_id'])
result['seg_result'] = seg_result
# 处理前片后片