aidlab/AiDA_Python
6
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Revert "design design batch"

Browse Source 
This reverts commit e6f0ee7f
This commit is contained in:
zhouchengrong
2024-12-11 13:51:22 +08:00
parent 731f07d252
commit 84fe2663f4
16 changed files with 24 additions and 279 deletions
Download Patch File Download Diff File Expand all files Collapse all files

21
app/service/design_batch/utils/synthesis_item.py
View File

@@ -79,11 +79,9 @@ 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
@@ -100,7 +98,7 @@ def synthesis(data, size, basic_info):
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]
top_outer_mask = background + top_outer_mask
elif bottom and data[i]['name'] in ["trousers_front", "skirt_front", "bottoms_front", "dress_front"]:
# bottom = False
bottom = False
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
@@ -111,23 +109,10 @@ 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:
@@ -200,14 +185,12 @@ def update_base_size_priority(layers, size):
# 计算透明背景图片的宽度
min_x = min(info['position'][1] for info in layers)
x_list = []
new_height = 700
for info in layers:
if info['image'] is not None:
x_list.append(info['position'][1] + info['image'].width)
if info['name'] == 'mannequin':
new_height = info['image'].height
max_x = max(x_list)
new_width = max_x - min_x
new_height = 700
# 更新坐标
for info in layers:
info['adaptive_position'] = (info['position'][0], info['position'][1] - min_x)