feat（新功能）:
fix（修复bug）: 修复print_painting.py 印花通道为RGB时 出现的偏移越界问题 docs（文档变更）: refactor（重构）: test(增加测试):
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zchengrong
@@ -55,90 +55,89 @@ class PrintPainting:
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mask_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
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for i in range(len(single_print['print_path_list'])):
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image, image_mode = self.read_image(single_print['print_path_list'][i])
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if image_mode == "RGBA":
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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]))
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mask = image.split()[3]
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resized_source = image.resize(new_size)
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resized_source_mask = mask.resize(new_size)
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if image_mode == "RGB":
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image_rgba = cv2.cvtColor(image, cv2.COLOR_BGR2RGBA)
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image = Image.fromarray(image_rgba)
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rotated_resized_source = resized_source.rotate(-single_print['print_angle_list'][i])
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rotated_resized_source_mask = resized_source_mask.rotate(-single_print['print_angle_list'][i])
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source_image_pil = Image.fromarray(cv2.cvtColor(print_background, cv2.COLOR_BGR2RGB))
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source_image_pil_mask = Image.fromarray(cv2.cvtColor(mask_background, cv2.COLOR_BGR2RGB))
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source_image_pil.paste(rotated_resized_source, (int(single_print['location'][i][0]), int(single_print['location'][i][1])), rotated_resized_source)
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source_image_pil_mask.paste(rotated_resized_source_mask, (int(single_print['location'][i][0]), int(single_print['location'][i][1])), rotated_resized_source_mask)
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print_background = cv2.cvtColor(np.array(source_image_pil), cv2.COLOR_RGBA2BGR)
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mask_background = cv2.cvtColor(np.array(source_image_pil_mask), cv2.COLOR_RGBA2BGR)
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ret, mask_background = cv2.threshold(mask_background, 124, 255, cv2.THRESH_BINARY)
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else:
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mask = self.get_mask_inv(image)
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mask = np.expand_dims(mask, axis=2)
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mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
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mask = cv2.bitwise_not(mask)
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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])))
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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])))
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# 旋转后的坐标需要重新算
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rotate_mask, _ = self.img_rotate(mask, single_print['print_angle_list'][i])
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rotate_image, rotated_new_size = self.img_rotate(image, single_print['print_angle_list'][i])
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# 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)
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x, y = int(single_print['location'][i][0] - rotated_new_size[0]), int(single_print['location'][i][1] - rotated_new_size[1])
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image_x = print_background.shape[1]
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image_y = print_background.shape[0]
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print_x = rotate_image.shape[1]
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print_y = rotate_image.shape[0]
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# 有bug
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# if x + print_x > image_x:
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# rotate_image = rotate_image[:, :x + print_x - image_x]
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# rotate_mask = rotate_mask[:, :x + print_x - image_x]
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# #
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# if y + print_y > image_y:
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# rotate_image = rotate_image[:y + print_y - image_y]
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# rotate_mask = rotate_mask[:y + print_y - image_y]
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# 不能是并行
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# 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
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# 先挪 再判断 最后裁剪
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# 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
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if x <= 0:
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rotate_image = rotate_image[:, -x:]
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rotate_mask = rotate_mask[:, -x:]
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start_x = x = 0
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else:
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start_x = x
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if y <= 0:
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rotate_image = rotate_image[-y:, :]
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rotate_mask = rotate_mask[-y:, :]
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start_y = y = 0
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else:
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start_y = y
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# ------------------
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# 如果print-size大于image-size 则需要裁剪print
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if x + print_x > image_x:
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rotate_image = rotate_image[:, :image_x - x]
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rotate_mask = rotate_mask[:, :image_x - x]
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if y + print_y > image_y:
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rotate_image = rotate_image[:image_y - y, :]
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rotate_mask = rotate_mask[:image_y - y, :]
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# 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)
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# 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)
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# mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = rotate_mask
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# print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = rotate_image
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mask_background = self.stack_prin(mask_background, result['pattern_image'], rotate_mask, start_y, y, start_x, x)
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print_background = self.stack_prin(print_background, result['pattern_image'], rotate_image, start_y, y, start_x, x)
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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]))
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mask = image.split()[3]
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resized_source = image.resize(new_size)
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resized_source_mask = mask.resize(new_size)
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rotated_resized_source = resized_source.rotate(-single_print['print_angle_list'][i])
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rotated_resized_source_mask = resized_source_mask.rotate(-single_print['print_angle_list'][i])
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source_image_pil = Image.fromarray(cv2.cvtColor(print_background, cv2.COLOR_BGR2RGB))
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source_image_pil_mask = Image.fromarray(cv2.cvtColor(mask_background, cv2.COLOR_BGR2RGB))
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source_image_pil.paste(rotated_resized_source, (int(single_print['location'][i][0]), int(single_print['location'][i][1])), rotated_resized_source)
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source_image_pil_mask.paste(rotated_resized_source_mask, (int(single_print['location'][i][0]), int(single_print['location'][i][1])), rotated_resized_source_mask)
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print_background = cv2.cvtColor(np.array(source_image_pil), cv2.COLOR_RGBA2BGR)
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mask_background = cv2.cvtColor(np.array(source_image_pil_mask), cv2.COLOR_RGBA2BGR)
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ret, mask_background = cv2.threshold(mask_background, 124, 255, cv2.THRESH_BINARY)
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# else:
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# mask = self.get_mask_inv(image)
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# mask = np.expand_dims(mask, axis=2)
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# mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
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# mask = cv2.bitwise_not(mask)
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#
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# 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])))
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# 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])))
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# # 旋转后的坐标需要重新算
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# rotate_mask, _ = self.img_rotate(mask, single_print['print_angle_list'][i])
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# rotate_image, rotated_new_size = self.img_rotate(image, single_print['print_angle_list'][i])
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# # 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)
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# x, y = int(single_print['location'][i][0] - rotated_new_size[0]), int(single_print['location'][i][1] - rotated_new_size[1])
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#
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# image_x = print_background.shape[1] # 底图宽
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# image_y = print_background.shape[0] # 底图高
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# print_x = rotate_image.shape[1] #印花宽
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# print_y = rotate_image.shape[0] #印花高
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#
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# # 有bug
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# # if x + print_x > image_x:
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# # rotate_image = rotate_image[:, :x + print_x - image_x]
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# # rotate_mask = rotate_mask[:, :x + print_x - image_x]
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# # #
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# # if y + print_y > image_y:
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# # rotate_image = rotate_image[:y + print_y - image_y]
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# # rotate_mask = rotate_mask[:y + print_y - image_y]
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#
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# # 不能是并行
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# # 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
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# # 先挪 再判断 最后裁剪
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#
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# # 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
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# if x <= 0: # 如果X轴偏移量小于0，说明印花需要被裁剪至合适大小 或当X轴偏移量大于印花宽度时，裁剪后的印花宽度为0
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# rotate_image = rotate_image[:, -x:]
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# rotate_mask = rotate_mask[:, -x:]
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# start_x = x = 0
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# else:
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# start_x = x
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#
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# if y <= 0:
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# rotate_image = rotate_image[-y:, :]
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# rotate_mask = rotate_mask[-y:, :]
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# start_y = y = 0
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# else:
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# start_y = y
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#
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# # ------------------
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# # 如果print-size大于image-size 则需要裁剪print
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#
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# if x + print_x > image_x:
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# rotate_image = rotate_image[:, :image_x - x]
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# rotate_mask = rotate_mask[:, :image_x - x]
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#
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# if y + print_y > image_y:
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# rotate_image = rotate_image[:image_y - y, :]
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# rotate_mask = rotate_mask[:image_y - y, :]
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#
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# # 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)
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# # 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)
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#
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# # mask_background[start_y:y + rotate_mask.shape[0], start_x:x + rotate_mask.shape[1]] = rotate_mask
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# # print_background[start_y:y + rotate_image.shape[0], start_x:x + rotate_image.shape[1]] = rotate_image
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# mask_background = self.stack_prin(mask_background, result['pattern_image'], rotate_mask, start_y, y, start_x, x)
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# print_background = self.stack_prin(print_background, result['pattern_image'], rotate_image, start_y, y, start_x, x)
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# gray_image = cv2.cvtColor(mask_background, cv2.COLOR_BGR2GRAY)
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# print_background = cv2.bitwise_and(print_background, print_background, mask=gray_image)
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