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| Author | SHA1 | Date | |
|---|---|---|---|
| 9db2f96557 | |||
| cc2404831d | |||
| 6892361050 | |||
| f0b73d5fc1 |
@@ -7,7 +7,7 @@ jobs:
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runs-on: ubuntu-latest
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runs-on: ubuntu-latest
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env:
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env:
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REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Prod
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REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/AiDA_Prod
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steps:
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steps:
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- name: 1.检出代码
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- name: 1.检出代码
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@@ -27,7 +27,7 @@ class NoSegPrintPainting:
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# 获取平铺 + 旋转 的overall print
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# 获取平铺 + 旋转 的overall print
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painting_dict = self.painting_collection(painting_dict, overall_print)
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painting_dict = self.painting_collection(painting_dict, overall_print)
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result['no_seg_sketch_overall'] = result['no_seg_sketch_print'] = self.printpaint(result, painting_dict, print_=True)
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result['no_seg_sketch_overall'] = result['no_seg_sketch_print'] = self.printpaint(result, painting_dict, print_=True)
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result['pattern_image'] = result['no_seg_sketch_overall']
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# result['pattern_image'] = result['no_seg_sketch_overall']
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if single_print:
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if single_print:
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print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
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print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
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@@ -166,15 +166,17 @@ class NoSegPrintPainting:
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dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
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dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
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dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
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dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
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gap = print_dict.get('gap', [[0, 0]])[0]
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gap = print_dict.get('gap', [[0, 0]])[0]
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painting_dict['tile_print'] = tile_image(pattern=print_['image'],
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painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
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dim=dim_pattern,
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mask=print_['mask'],
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gap_x=gap[0],
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dim=dim_pattern,
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gap_y=gap[1],
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gap_x=gap[0],
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canvas_h=painting_dict['dim_image_h'],
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gap_y=gap[1],
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canvas_w=painting_dict['dim_image_w'],
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canvas_h=painting_dict['dim_image_h'],
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location=painting_dict['location'],
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canvas_w=painting_dict['dim_image_w'],
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angle=int(print_.get('print_angle_list', [0])[0]))
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location=painting_dict['location'],
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painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
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angle=int(print_.get('print_angle_list', [0])[0]))
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# painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
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# painting_dict['mask_inv_print'] = self.get_mask_inv(painting_dict['tile_print'])
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return painting_dict
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return painting_dict
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def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
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def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
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@@ -255,10 +257,15 @@ class NoSegPrintPainting:
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image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
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image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
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# 判断图片格式,如果是RGBA 则贴在一张纯白图片上 防止透明转黑
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# 判断图片格式,如果是RGBA 则贴在一张纯白图片上 防止透明转黑
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if image.mode == "RGBA":
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if image.mode == "RGBA":
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mask_pil = image.split()[3]
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new_background = Image.new('RGB', image.size, (255, 255, 255))
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new_background = Image.new('RGB', image.size, (255, 255, 255))
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new_background.paste(image, mask=image.split()[3])
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new_background.paste(image, mask=image.split()[3])
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image = new_background
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image = new_background
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else:
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mask_pil = Image.new('L', image.size, 255) # L=灰度图,255=纯白
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print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
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print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
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print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
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return print_dict
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return print_dict
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def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
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def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
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@@ -408,9 +415,12 @@ class NoSegPrintPainting:
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return cropped_img
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return cropped_img
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def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
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def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
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"""
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"""
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按照指定的 X/Y 间距平铺印花,并支持旋转
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按照指定的 X/Y 间距平铺印花,并支持旋转
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【修改版】以被平铺图案的【中心】作为平铺基准点
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:param location: [[center_y, center_x]] → 第一个图案中心的坐标
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:param angle: 旋转角度 (度数, 逆时针)
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:param angle: 旋转角度 (度数, 逆时针)
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"""
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"""
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# 1. 确保输入是 RGBA
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# 1. 确保输入是 RGBA
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@@ -422,35 +432,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
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rotated_p = rotate_image(resized_p, angle)
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rotated_p = rotate_image(resized_p, angle)
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p_h, p_w = rotated_p.shape[:2]
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p_h, p_w = rotated_p.shape[:2]
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# 3. 创建透明单元格
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# 3. 创建透明单元格(图案放在单元格中心)
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cell_h, cell_w = p_h + gap_y, p_w + gap_x
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cell_h = p_h + gap_y
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cell_w = p_w + gap_x
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unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
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unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
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unit_cell[:p_h, :p_w, :] = rotated_p
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# 计算图案在单元格中的左上角位置(让图案居中)
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start_y = (cell_h - p_h) // 2
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start_x = (cell_w - p_w) // 2
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unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
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# 4. 执行平铺
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# 4. 执行平铺
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tiles_y = (canvas_h // cell_h) + 2
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tiles_y = (canvas_h // cell_h) + 3 # 多加一点余量更安全
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tiles_x = (canvas_w // cell_w) + 2
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tiles_x = (canvas_w // cell_w) + 3
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full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
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full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
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# 5. 裁剪平铺层
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# 5. 计算偏移(关键修改:以中心为基准)
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offset_x = int(location[0][1] % cell_w)
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center_y, center_x = location[0][0], location[0][1] # 第一个图案的中心位置
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offset_y = int(location[0][0] % cell_h)
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# 计算从哪个位置开始裁剪,才能让中心落在指定坐标
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offset_y = int((center_y - (p_h // 2)) % cell_h)
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offset_x = int((center_x - (p_w // 2)) % cell_w)
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tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
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tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
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offset_x: offset_x + canvas_w]
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offset_x: offset_x + canvas_w]
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# 6. 创建纯白色背景并合成
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# 6. 创建纯白色背景并合成(保持你原来的风格)
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# 创建一个纯白色的 BGR 画布
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white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
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white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
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# 分离平铺层的颜色通道和 Alpha 通道
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tiled_bgr = tiled_layer[:, :, :3]
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tiled_bgr = tiled_layer[:, :, :3]
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alpha_mask = tiled_layer[:, :, 3] / 255.0 # 归一化到 0-1
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alpha_mask = tiled_layer[:, :, 3] / 255.0
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alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask]) # 扩展到 3 通道
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alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
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# 执行 Alpha 混合:结果 = 平铺层 * alpha + 背景 * (1 - alpha)
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tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
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result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
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return result
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# ====================== 处理 Mask ======================
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# Mask 也同样居中处理
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resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
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rotated_mask = rotate_image(resized_mask, angle) # 注意:mask也需要旋转
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unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
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unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
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full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
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tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
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offset_x: offset_x + canvas_w]
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return tiled_print, cv2.bitwise_not(tiled_mask)
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def rotate_image(image, angle):
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def rotate_image(image, angle):
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@@ -41,7 +41,7 @@ class PrintPainting:
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if overall_print['print_path_list']:
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if overall_print['print_path_list']:
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overall_print['location'][0] = [x * y for x, y in zip(overall_print['location'][0], result['resize_scale'])]
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overall_print['location'][0] = [x * y for x, y in zip(overall_print['location'][0], result['resize_scale'])]
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painting_dict = {'dim_image_h': result['pattern_image'].shape[0], 'dim_image_w': result['pattern_image'].shape[1]}
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painting_dict = {'dim_image_h': result['pattern_image'].shape[0], 'dim_image_w': result['pattern_image'].shape[1]}
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result['print_image'] = result['pattern_image']
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result['print_image'] = result['pattern_image'].copy()
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# 获取平铺 + 旋转 的overall print
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# 获取平铺 + 旋转 的overall print
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painting_dict = self.painting_collection(painting_dict, overall_print)
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painting_dict = self.painting_collection(painting_dict, overall_print)
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result['print_image'] = self.printpaint(result, painting_dict, print_=True)
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result['print_image'] = self.printpaint(result, painting_dict, print_=True)
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@@ -229,15 +229,15 @@ class PrintPainting:
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dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
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dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
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dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
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dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
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gap = print_dict.get('gap', [[0, 0]])[0]
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gap = print_dict.get('gap', [[0, 0]])[0]
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painting_dict['tile_print'] = tile_image(pattern=print_['image'],
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painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
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dim=dim_pattern,
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mask=print_['mask'],
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gap_x=gap[0],
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dim=dim_pattern,
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gap_y=gap[1],
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gap_x=gap[0],
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canvas_h=painting_dict['dim_image_h'],
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gap_y=gap[1],
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canvas_w=painting_dict['dim_image_w'],
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canvas_h=painting_dict['dim_image_h'],
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location=painting_dict['location'],
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canvas_w=painting_dict['dim_image_w'],
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angle=int(print_.get('print_angle_list', [0])[0]))
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location=painting_dict['location'],
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painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
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angle=int(print_.get('print_angle_list', [0])[0]))
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return painting_dict
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return painting_dict
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def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
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def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
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@@ -318,10 +318,15 @@ class PrintPainting:
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image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
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image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
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# 判断图片格式,如果是RGBA 则贴在一张纯白图片上 防止透明转黑
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# 判断图片格式,如果是RGBA 则贴在一张纯白图片上 防止透明转黑
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if image.mode == "RGBA":
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if image.mode == "RGBA":
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mask_pil = image.split()[3]
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new_background = Image.new('RGB', image.size, (255, 255, 255))
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new_background = Image.new('RGB', image.size, (255, 255, 255))
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new_background.paste(image, mask=image.split()[3])
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new_background.paste(image, mask=image.split()[3])
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image = new_background
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image = new_background
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else:
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mask_pil = Image.new('L', image.size, 255) # L=灰度图,255=纯白
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print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
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print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
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print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
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return print_dict
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return print_dict
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def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
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def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
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@@ -471,9 +476,12 @@ class PrintPainting:
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return cropped_img
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return cropped_img
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def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
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def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
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"""
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"""
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按照指定的 X/Y 间距平铺印花,并支持旋转
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按照指定的 X/Y 间距平铺印花,并支持旋转
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【修改版】以被平铺图案的【中心】作为平铺基准点
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:param location: [[center_y, center_x]] → 第一个图案中心的坐标
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:param angle: 旋转角度 (度数, 逆时针)
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:param angle: 旋转角度 (度数, 逆时针)
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"""
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"""
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# 1. 确保输入是 RGBA
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# 1. 确保输入是 RGBA
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@@ -485,35 +493,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
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rotated_p = rotate_image(resized_p, angle)
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rotated_p = rotate_image(resized_p, angle)
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p_h, p_w = rotated_p.shape[:2]
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p_h, p_w = rotated_p.shape[:2]
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# 3. 创建透明单元格
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# 3. 创建透明单元格(图案放在单元格中心)
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cell_h, cell_w = p_h + gap_y, p_w + gap_x
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cell_h = p_h + gap_y
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cell_w = p_w + gap_x
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unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
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unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
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unit_cell[:p_h, :p_w, :] = rotated_p
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# 计算图案在单元格中的左上角位置(让图案居中)
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start_y = (cell_h - p_h) // 2
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start_x = (cell_w - p_w) // 2
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unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
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# 4. 执行平铺
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# 4. 执行平铺
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tiles_y = (canvas_h // cell_h) + 2
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tiles_y = (canvas_h // cell_h) + 3 # 多加一点余量更安全
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tiles_x = (canvas_w // cell_w) + 2
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tiles_x = (canvas_w // cell_w) + 3
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full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
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full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
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# 5. 裁剪平铺层
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# 5. 计算偏移(关键修改:以中心为基准)
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offset_x = int(location[0][1] % cell_w)
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center_y, center_x = location[0][0], location[0][1] # 第一个图案的中心位置
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offset_y = int(location[0][0] % cell_h)
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|
||||||
|
# 计算从哪个位置开始裁剪,才能让中心落在指定坐标
|
||||||
|
offset_y = int((center_y - (p_h // 2)) % cell_h)
|
||||||
|
offset_x = int((center_x - (p_w // 2)) % cell_w)
|
||||||
|
|
||||||
tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
|
tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
|
||||||
offset_x: offset_x + canvas_w]
|
offset_x: offset_x + canvas_w]
|
||||||
|
|
||||||
# 6. 创建纯白色背景并合成
|
# 6. 创建纯白色背景并合成(保持你原来的风格)
|
||||||
# 创建一个纯白色的 BGR 画布
|
|
||||||
white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
|
white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
|
||||||
|
|
||||||
# 分离平铺层的颜色通道和 Alpha 通道
|
|
||||||
tiled_bgr = tiled_layer[:, :, :3]
|
tiled_bgr = tiled_layer[:, :, :3]
|
||||||
alpha_mask = tiled_layer[:, :, 3] / 255.0 # 归一化到 0-1
|
alpha_mask = tiled_layer[:, :, 3] / 255.0
|
||||||
alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask]) # 扩展到 3 通道
|
alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
|
||||||
|
|
||||||
# 执行 Alpha 混合:结果 = 平铺层 * alpha + 背景 * (1 - alpha)
|
tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
|
||||||
result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
|
|
||||||
|
|
||||||
return result
|
# ====================== 处理 Mask ======================
|
||||||
|
# Mask 也同样居中处理
|
||||||
|
resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
|
||||||
|
rotated_mask = rotate_image(resized_mask, angle) # 注意:mask也需要旋转
|
||||||
|
|
||||||
|
unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
|
||||||
|
unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
|
||||||
|
|
||||||
|
full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
|
||||||
|
tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
|
||||||
|
offset_x: offset_x + canvas_w]
|
||||||
|
|
||||||
|
return tiled_print, cv2.bitwise_not(tiled_mask)
|
||||||
|
|
||||||
|
|
||||||
def rotate_image(image, angle):
|
def rotate_image(image, angle):
|
||||||
|
|||||||
Reference in New Issue
Block a user