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fix  design ifsingle为true 但 没有print的 异常检测取消
This commit is contained in:
zhouchengrong
2024-06-24 15:31:39 +08:00
parent 1db39d4c39
commit d827147e8a
1 changed files with 89 additions and 91 deletions
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180
app/service/design/items/pipelines/painting.py
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@@ -99,111 +99,109 @@ class PrintPainting(object):
elif result['print']["location"] == [] or result['print']["location"] is None: elif result['print']["location"] == [] or result['print']["location"] is None:
result['print']["location"] = [[0, 0]] result['print']["location"] = [[0, 0]]
if result['print']['IfSingle']: if result['print']['IfSingle']:
if len(result['print']['print_path_list']) == 0: if len(result['print']['print_path_list']) > 0:
raise ValueError('When there is no printing, ifsingle must be false') 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)
# print_background = np.full((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), 255, dtype=np.uint8)
for i in range(len(result['print']['print_path_list'])):
image, image_mode = self.read_image(result['print']['print_path_list'][i])
if image_mode == "RGBA":
new_size = (int(image.width * result['print']['print_scale_list'][i]), int(image.height * result['print']['print_scale_list'][i]))
print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8) mask = image.split()[3]
mask_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8) resized_source = image.resize(new_size)
# print_background = np.full((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), 255, dtype=np.uint8) resized_source_mask = mask.resize(new_size)
for i in range(len(result['print']['print_path_list'])):
image, image_mode = self.read_image(result['print']['print_path_list'][i])
if image_mode == "RGBA":
new_size = (int(image.width * result['print']['print_scale_list'][i]), int(image.height * result['print']['print_scale_list'][i]))
mask = image.split()[3] rotated_resized_source = resized_source.rotate(-result['print']['print_angle_list'][i])
resized_source = image.resize(new_size) rotated_resized_source_mask = resized_source_mask.rotate(-result['print']['print_angle_list'][i])
resized_source_mask = mask.resize(new_size)
rotated_resized_source = resized_source.rotate(-result['print']['print_angle_list'][i]) source_image_pil = Image.fromarray(cv2.cvtColor(print_background, cv2.COLOR_BGR2RGB))
rotated_resized_source_mask = resized_source_mask.rotate(-result['print']['print_angle_list'][i]) source_image_pil_mask = Image.fromarray(cv2.cvtColor(mask_background, cv2.COLOR_BGR2RGB))
source_image_pil = Image.fromarray(cv2.cvtColor(print_background, cv2.COLOR_BGR2RGB)) source_image_pil.paste(rotated_resized_source, (int(result['print']['location'][i][0]), int(result['print']['location'][i][1])), rotated_resized_source)
source_image_pil_mask = Image.fromarray(cv2.cvtColor(mask_background, cv2.COLOR_BGR2RGB)) source_image_pil_mask.paste(rotated_resized_source_mask, (int(result['print']['location'][i][0]), int(result['print']['location'][i][1])), rotated_resized_source_mask)
source_image_pil.paste(rotated_resized_source, (int(result['print']['location'][i][0]), int(result['print']['location'][i][1])), rotated_resized_source) print_background = cv2.cvtColor(np.array(source_image_pil), cv2.COLOR_RGBA2BGR)
source_image_pil_mask.paste(rotated_resized_source_mask, (int(result['print']['location'][i][0]), int(result['print']['location'][i][1])), rotated_resized_source_mask) mask_background = cv2.cvtColor(np.array(source_image_pil_mask), cv2.COLOR_RGBA2BGR)
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)
else:
mask = self.get_mask_inv(image)
mask = np.expand_dims(mask, axis=2)
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
mask = cv2.bitwise_not(mask)
# 旋转后的坐标需要重新算
rotate_mask, _ = self.img_rotate(mask, result['print']['print_angle_list'][i], result['print']['print_scale_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, result['print']['print_angle_list'][i], result['print']['print_scale_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(result['print']['location'][i][0] - rotated_new_size[0]), int(result['print']['location'][i][1] - rotated_new_size[1])
image_x = print_background.shape[1]
image_y = print_background.shape[0]
print_x = rotate_image.shape[1]
print_y = rotate_image.shape[0]
# 有bug
# if x + print_x > image_x:
# rotate_image = rotate_image[:, :x + print_x - image_x]
# rotate_mask = rotate_mask[:, :x + print_x - image_x]
# #
# if y + print_y > image_y:
# rotate_image = rotate_image[:y + print_y - image_y]
# rotate_mask = rotate_mask[:y + print_y - image_y]
# 不能是并行
# 当前第一轮的if （108以及115）是判断有没有过下界和右界。第二轮的是判断左上有没有超出。 如果这个样子的话，先裁了右边，再左移，region就会有问题
# 先挪 再判断 最后裁剪
# 如果print旋转了 或者 print贴边了 则需要判断 判断左界和上界是否小于0
if x <= 0:
rotate_image = rotate_image[:, -x:]
rotate_mask = rotate_mask[:, -x:]
start_x = x = 0
else: else:
start_x = x mask = self.get_mask_inv(image)
mask = np.expand_dims(mask, axis=2)
mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
mask = cv2.bitwise_not(mask)
# 旋转后的坐标需要重新算
rotate_mask, _ = self.img_rotate(mask, result['print']['print_angle_list'][i], result['print']['print_scale_list'][i])
rotate_image, rotated_new_size = self.img_rotate(image, result['print']['print_angle_list'][i], result['print']['print_scale_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(result['print']['location'][i][0] - rotated_new_size[0]), int(result['print']['location'][i][1] - rotated_new_size[1])
if y <= 0: image_x = print_background.shape[1]
rotate_image = rotate_image[-y:, :] image_y = print_background.shape[0]
rotate_mask = rotate_mask[-y:, :] print_x = rotate_image.shape[1]
start_y = y = 0 print_y = rotate_image.shape[0]
else:
start_y = y
# ------------------ # 有bug
# 如果print-size大于image-size 则需要裁剪print # if x + print_x > image_x:
# rotate_image = rotate_image[:, :x + print_x - image_x]
# rotate_mask = rotate_mask[:, :x + print_x - image_x]
# #
# if y + print_y > image_y:
# rotate_image = rotate_image[:y + print_y - image_y]
# rotate_mask = rotate_mask[:y + print_y - image_y]
if x + print_x > image_x: # 不能是并行
rotate_image = rotate_image[:, :image_x - x] # 当前第一轮的if （108以及115）是判断有没有过下界和右界。第二轮的是判断左上有没有超出。 如果这个样子的话，先裁了右边，再左移，region就会有问题
rotate_mask = rotate_mask[:, :image_x - x] # 先挪 再判断 最后裁剪
if y + print_y > image_y: # 如果print旋转了 或者 print贴边了 则需要判断 判断左界和上界是否小于0
rotate_image = rotate_image[:image_y - y, :] if x <= 0:
rotate_mask = rotate_mask[:image_y - y, :] rotate_image = rotate_image[:, -x:]
rotate_mask = rotate_mask[:, -x:]
start_x = x = 0
else:
start_x = x
# mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = cv2.bitwise_xor(mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]], rotate_mask) if y <= 0:
# print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = cv2.add(print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]], rotate_image) rotate_image = rotate_image[-y:, :]
rotate_mask = rotate_mask[-y:, :]
start_y = y = 0
else:
start_y = y
# mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = rotate_mask # ------------------
# print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = rotate_image # 如果print-size大于image-size 则需要裁剪print
mask_background = self.stack_prin(mask_background, result['pattern_image'], rotate_mask, start_y, y, start_x, x)
print_background = self.stack_prin(print_background, result['pattern_image'], rotate_image, start_y, y, start_x, x)
# gray_image = cv2.cvtColor(mask_background, cv2.COLOR_BGR2GRAY) if x + print_x > image_x:
# print_background = cv2.bitwise_and(print_background, print_background, mask=gray_image) rotate_image = rotate_image[:, :image_x - x]
rotate_mask = rotate_mask[:, :image_x - x]
print_mask = cv2.bitwise_and(result['mask'], cv2.cvtColor(mask_background, cv2.COLOR_BGR2GRAY)) if y + print_y > image_y:
img_fg = cv2.bitwise_or(print_background, print_background, mask=print_mask) rotate_image = rotate_image[:image_y - y, :]
img_bg = cv2.bitwise_and(result['pattern_image'], result['pattern_image'], mask=cv2.bitwise_not(print_mask)) rotate_mask = rotate_mask[:image_y - y, :]
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) # mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = cv2.bitwise_xor(mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]], rotate_mask)
img_fg = (img_fg * (mask_mo / 255) * (gray_mo / 255)).astype(np.uint8) # print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = cv2.add(print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]], rotate_image)
result['final_image'] = cv2.add(img_bg, img_fg)
canvas = np.full_like(result['final_image'], 255) # mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = rotate_mask
temp_bg = np.expand_dims(cv2.bitwise_not(result['mask']), axis=2).repeat(3, axis=2) # print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = rotate_image
tmp1 = (canvas * (temp_bg / 255)).astype(np.uint8) mask_background = self.stack_prin(mask_background, result['pattern_image'], rotate_mask, start_y, y, start_x, x)
temp_fg = np.expand_dims(result['mask'], axis=2).repeat(3, axis=2) print_background = self.stack_prin(print_background, result['pattern_image'], rotate_image, start_y, y, start_x, x)
tmp2 = (result['final_image'] * (temp_fg / 255)).astype(np.uint8)
result['single_image'] = cv2.add(tmp1, tmp2) # gray_image = cv2.cvtColor(mask_background, cv2.COLOR_BGR2GRAY)
# print_background = cv2.bitwise_and(print_background, print_background, mask=gray_image)
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)
img_bg = cv2.bitwise_and(result['pattern_image'], result['pattern_image'], mask=cv2.bitwise_not(print_mask))
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)
else: else:
painting_dict = {} painting_dict = {}
painting_dict['dim_image_h'], painting_dict['dim_image_w'] = result['pattern_image'].shape[0:2] painting_dict['dim_image_h'], painting_dict['dim_image_w'] = result['pattern_image'].shape[0:2]