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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):
This commit is contained in:
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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95
app/service/design_batch/pipeline/print_painting.py
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@@ -15,8 +15,25 @@ class PrintPainting:
single_print = result['print']['single']
overall_print = result['print']['overall']
element_print = result['print']['element']
partial_path = result['print']['partial'] if 'partial' in result['print'] else None
result['single_image'] = None
result['print_image'] = None
# TODO 给result['pattern_image'] resize 到resize_scale的大小
# TODO 给result['mask'] resize 到resize_scale的大小
if result['resize_scale'][0] == 1.0 and result['resize_scale'][1] == 1.0:
pass
else:
height, width = result['pattern_image'].shape[:2]
new_width = int(width * result['resize_scale'][0])
new_height = int(height * result['resize_scale'][1])
result['pattern_image'] = cv2.resize(result['pattern_image'], (new_width, new_height))
result['final_image'] = cv2.resize(result['final_image'], (new_width, new_height))
result['mask'] = cv2.resize(result['mask'], (new_width, new_height))
result['gray'] = cv2.resize(result['gray'], (new_width, new_height))
print(1)
if overall_print['print_path_list']:
painting_dict = {'dim_image_h': result['pattern_image'].shape[0], 'dim_image_w': result['pattern_image'].shape[1]}
result['print_image'] = result['pattern_image']
@@ -39,7 +56,7 @@ class PrintPainting:
for i in range(len(single_print['print_path_list'])):
image, image_mode = self.read_image(single_print['print_path_list'][i])
if image_mode == "RGBA":
new_size = (int(image.width * single_print['print_scale_list'][i]), int(image.height * single_print['print_scale_list'][i]))
new_size = (int(result['pattern_image'].shape[1] * single_print['print_scale_list'][i][0]), int(result['pattern_image'].shape[0] * single_print['print_scale_list'][i][1]))
mask = image.split()[3]
resized_source = image.resize(new_size)
@@ -62,9 +79,12 @@ class PrintPainting:
mask = np.expand_dims(mask, axis=2)
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
mask = cv2.bitwise_not(mask)
mask = cv2.resize(mask, (int(result['final_image'].shape[1] * single_print['print_scale_list'][i][0]), int(result['final_image'].shape[0] * single_print['print_scale_list'][i][1])))
image = cv2.resize(image, (int(result['final_image'].shape[1] * single_print['print_scale_list'][i][0]), int(result['final_image'].shape[0] * single_print['print_scale_list'][i][1])))
# 旋转后的坐标需要重新算
rotate_mask, _ = self.img_rotate(mask, single_print['print_angle_list'][i], single_print['print_scale_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, single_print['print_angle_list'][i], single_print['print_scale_list'][i])
rotate_mask, _ = self.img_rotate(mask, single_print['print_angle_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, single_print['print_angle_list'][i])
# x, y = int(result['print']['location'][i][0] - rotated_new_size[0] - (rotate_mask.shape[0] - image.shape[0]) / 2), int(result['print']['location'][i][1] - rotated_new_size[1] - (rotate_mask.shape[1] - image.shape[1]) / 2)
x, y = int(single_print['location'][i][0] - rotated_new_size[0]), int(single_print['location'][i][1] - rotated_new_size[1])
@@ -143,7 +163,7 @@ class PrintPainting:
for i in range(len(element_print['element_path_list'])):
image, image_mode = self.read_image(element_print['element_path_list'][i])
if image_mode == "RGBA":
new_size = (int(image.width * element_print['element_scale_list'][i]), int(image.height * element_print['element_scale_list'][i]))
new_size = (int(result['final_image'].shape[1] * element_print['element_scale_list'][i][0]), int(result['final_image'].shape[0] * element_print['element_scale_list'][i][1]))
mask = image.split()[3]
resized_source = image.resize(new_size)
@@ -165,9 +185,11 @@ class PrintPainting:
mask = np.expand_dims(mask, axis=2)
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
mask = cv2.bitwise_not(mask)
mask = cv2.resize(mask, (int(result['final_image'].shape[1] * single_print['print_scale_list'][i][0]), int(result['final_image'].shape[0] * single_print['print_scale_list'][i][1])))
image = cv2.resize(image, (int(result['final_image'].shape[1] * single_print['print_scale_list'][i][0]), int(result['final_image'].shape[0] * single_print['print_scale_list'][i][1])))
# 旋转后的坐标需要重新算
rotate_mask, _ = self.img_rotate(mask, element_print['element_angle_list'][i], element_print['element_scale_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, element_print['element_angle_list'][i], element_print['element_scale_list'][i])
rotate_mask, _ = self.img_rotate(mask, element_print['element_angle_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, element_print['element_angle_list'][i])
# x, y = int(result['print']['location'][i][0] - rotated_new_size[0] - (rotate_mask.shape[0] - image.shape[0]) / 2), int(result['print']['location'][i][1] - rotated_new_size[1] - (rotate_mask.shape[1] - image.shape[1]) / 2)
x, y = int(element_print['location'][i][0] - rotated_new_size[0]), int(element_print['location'][i][1] - rotated_new_size[1])
@@ -241,6 +263,45 @@ class PrintPainting:
temp_fg = np.expand_dims(result['mask'], axis=2).repeat(3, axis=2)
tmp2 = (result['final_image'] * (temp_fg / 255)).astype(np.uint8)
result['single_image'] = cv2.add(tmp1, tmp2)
if partial_path:
print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
mask_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
image, image_mode = self.read_image(partial_path)
if image_mode == "RGBA":
new_size = (result['pattern_image'].shape[1], result['pattern_image'].shape[0])
mask = image.split()[3]
resized_source = image.resize(new_size)
resized_source_mask = mask.resize(new_size)
# rotated_resized_source = resized_source.rotate(-partial_print['print_angle_list'][i])
# rotated_resized_source_mask = resized_source_mask.rotate(-partial_print['print_angle_list'][i])
source_image_pil = Image.fromarray(cv2.cvtColor(print_background, cv2.COLOR_BGR2RGB))
source_image_pil_mask = Image.fromarray(cv2.cvtColor(mask_background, cv2.COLOR_BGR2RGB))
source_image_pil.paste(resized_source, (0, 0), resized_source)
source_image_pil_mask.paste(resized_source_mask, (0, 0), resized_source_mask)
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)
ret, mask_background = cv2.threshold(mask_background, 124, 255, cv2.THRESH_BINARY)
print_mask = cv2.bitwise_and(result['mask'], cv2.cvtColor(mask_background, cv2.COLOR_BGR2GRAY))
img_fg = cv2.bitwise_or(print_background, print_background, mask=print_mask)
# TODO element 丢失信息
three_channel_image = cv2.merge([cv2.bitwise_not(print_mask), cv2.bitwise_not(print_mask), cv2.bitwise_not(print_mask)])
img_bg = cv2.bitwise_and(result['final_image'], three_channel_image)
# mask_mo = np.expand_dims(print_mask, axis=2).repeat(3, axis=2)
# gray_mo = np.expand_dims(result['gray'], axis=2).repeat(3, axis=2)
# img_fg = (img_fg * (mask_mo / 255) * (gray_mo / 255)).astype(np.uint8)
result['final_image'] = cv2.add(img_bg, img_fg)
canvas = np.full_like(result['final_image'], 255)
temp_bg = np.expand_dims(cv2.bitwise_not(result['mask']), axis=2).repeat(3, axis=2)
tmp1 = (canvas * (temp_bg / 255)).astype(np.uint8)
temp_fg = np.expand_dims(result['mask'], axis=2).repeat(3, axis=2)
tmp2 = (result['final_image'] * (temp_fg / 255)).astype(np.uint8)
result['single_image'] = cv2.add(tmp1, tmp2)
return result
@staticmethod
@@ -360,10 +421,10 @@ class PrintPainting:
return print_image
def get_print(self, print_dict):
if 'print_scale_list' not in print_dict.keys() or print_dict['print_scale_list'][0] < 0.3:
if 'print_scale_list' not in print_dict.keys() or print_dict['print_scale_list'][0][0] < 0.3:
print_dict['scale'] = 0.3
else:
print_dict['scale'] = print_dict['print_scale_list'][0]
print_dict['scale'] = print_dict['print_scale_list'][0][0]
bucket_name = print_dict['print_path_list'][0].split("/", 1)[0]
object_name = print_dict['print_path_list'][0].split("/", 1)[1]
@@ -386,8 +447,9 @@ class PrintPainting:
# y_offset = random.randint(0, image.shape[1] - image_size_w)
# 1.拿到偏移量后和resize后的print宽高取余 得到真正偏移量
x_offset = print_w - int(location[0][1] % print_w)
y_offset = print_w - int(location[0][0] % print_h)
# 偏移量增加2分之print.w 使坐标位于图中间 如果要位于左上角删除+ print_w // 2 即可
x_offset = print_w - int(location[0][1] % print_w) + print_w // 2
y_offset = print_h - int(location[0][0] % print_h) + print_h // 2
# y_offset = int(location[0][0])
# x_offset = int(location[0][1])
@@ -409,7 +471,7 @@ class PrintPainting:
return high, low
@staticmethod
def img_rotate(image, angel, scale):
def img_rotate(image, angel):
"""顺时针旋转图像任意角度
Args:
@@ -424,7 +486,7 @@ class PrintPainting:
center = (w // 2, h // 2)
# if type(angel) is not int:
# angel = 0
M = cv2.getRotationMatrix2D(center, -angel, scale)
M = cv2.getRotationMatrix2D(center, -angel, 1)
# 调整旋转后的图像长宽
rotated_h = int((w * np.abs(M[0, 1]) + (h * np.abs(M[0, 0]))))
rotated_w = int((h * np.abs(M[0, 1]) + (w * np.abs(M[0, 0]))))
@@ -433,7 +495,7 @@ class PrintPainting:
# 旋转图像
rotated_img = cv2.warpAffine(image, M, (rotated_w, rotated_h))
return rotated_img, ((rotated_img.shape[1] - image.shape[1] * scale) // 2, (rotated_img.shape[0] - image.shape[0] * scale) // 2)
return rotated_img, ((rotated_img.shape[1] - image.shape[1]) // 2, (rotated_img.shape[0] - image.shape[0]) // 2)
# return rotated_img, (0, 0)
@staticmethod
@@ -442,8 +504,11 @@ 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
@@ -455,7 +520,7 @@ 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