feat print overall 旋转

fix

app/service/design/items/pipelines/painting.py

@@ -204,7 +204,14 @@ class PrintPainting(object):
                 result['print_image'] = result['pattern_image']
             # print
             else:
-                painting_dict = self.painting_collection(painting_dict, result, print_trigger=True)
+                if result['print']['print_angle_list'][0] != 0:
+                    painting_dict = self.painting_collection(painting_dict, result, print_trigger=True)
+                    painting_dict['tile_print'] = self.rotate_crop_image(img=painting_dict['tile_print'], angle=result['print']['print_angle_list'][0], crop=True)
+                    # resize 到sketch大小
+                    painting_dict['tile_print'] = self.resize_and_crop(img=painting_dict['tile_print'], target_width=painting_dict['dim_image_w'], target_height=painting_dict['dim_image_h'])
+                    painting_dict['mask_inv_print'] = self.resize_and_crop(img=painting_dict['mask_inv_print'], target_width=painting_dict['dim_image_w'], target_height=painting_dict['dim_image_h'])
+                else:
+                    painting_dict = self.painting_collection(painting_dict, result, print_trigger=True)
                 result['print_image'] = self.printpaint(result, painting_dict, print_=True)
             result['final_image'] = result['print_image']
             canvas = np.full_like(result['final_image'], 255)
@@ -351,8 +358,13 @@ class PrintPainting(object):
             dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
             if not print_['IfSingle']:
                 self.random_seed = random.randint(0, 1000)
-                painting_dict['mask_inv_print'] = self.tile_image(single_mask_inv_print, dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'], trigger=True)
+                # 如果print 模式为overall 且 有角度的话 ， 组合的print为正方形，方便裁剪
-                painting_dict['tile_print'] = self.tile_image(print_['image'], dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'], trigger=True)
+                if result['print']['print_angle_list'][0] != 0:
+                    painting_dict['mask_inv_print'] = self.tile_image(single_mask_inv_print, dim_pattern, print_['scale'], dim_max, dim_max, painting_dict['location'], trigger=True)
+                    painting_dict['tile_print'] = self.tile_image(print_['image'], dim_pattern, print_['scale'], dim_max, dim_max, painting_dict['location'], trigger=True)
+                else:
+                    painting_dict['mask_inv_print'] = self.tile_image(single_mask_inv_print, dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'], trigger=True)
+                    painting_dict['tile_print'] = self.tile_image(print_['image'], dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'], trigger=True)
             else:
                 painting_dict['mask_inv_print'] = self.tile_image(single_mask_inv_print, dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'])
                 painting_dict['tile_print'] = self.tile_image(print_['image'], dim_pattern, print_['scale'], painting_dict['dim_image_h'], painting_dict['dim_image_w'], painting_dict['location'])
@@ -533,6 +545,52 @@ class PrintPainting(object):
         return rotated_img, ((rotated_img.shape[1] - image.shape[1] * scale) // 2, (rotated_img.shape[0] - image.shape[0] * scale) // 2)
         # return rotated_img, (0, 0)
 
+    @staticmethod
+    def rotate_crop_image(img, angle, crop):
+        """
+        angle: 旋转的角度
+        crop: 是否需要进行裁剪，布尔向量
+        """
+        crop_image = lambda img, x0, y0, w, h: img[y0:y0 + h, x0:x0 + w]
+        w, h = img.shape[:2]
+        # 旋转角度的周期是360°
+        angle %= 360
+        # 计算仿射变换矩阵
+        M_rotation = cv2.getRotationMatrix2D((w / 2, h / 2), angle, 1)
+        # 得到旋转后的图像
+        img_rotated = cv2.warpAffine(img, M_rotation, (w, h))
+
+        # 如果需要去除黑边
+        if crop:
+            # 裁剪角度的等效周期是180°
+            angle_crop = angle % 180
+            if angle > 90:
+                angle_crop = 180 - angle_crop
+            # 转化角度为弧度
+            theta = angle_crop * np.pi / 180
+            # 计算高宽比
+            hw_ratio = float(h) / float(w)
+            # 计算裁剪边长系数的分子项
+            tan_theta = np.tan(theta)
+            numerator = np.cos(theta) + np.sin(theta) * np.tan(theta)
+
+            # 计算分母中和高宽比相关的项
+            r = hw_ratio if h > w else 1 / hw_ratio
+            # 计算分母项
+            denominator = r * tan_theta + 1
+            # 最终的边长系数
+            crop_mult = numerator / denominator
+
+            # 得到裁剪区域
+            w_crop = int(crop_mult * w)
+            h_crop = int(crop_mult * h)
+            x0 = int((w - w_crop) / 2)
+            y0 = int((h - h_crop) / 2)
+
+            img_rotated = crop_image(img_rotated, x0, y0, w_crop, h_crop)
+
+        return img_rotated
+
     @staticmethod
     def read_image(image_url):
         image = oss_get_image(bucket=image_url.split("/", 1)[0], object_name=image_url.split("/", 1)[1], data_type="cv2")
@@ -544,26 +602,33 @@ class PrintPainting(object):
             image_mode = "RGB"
         return image, image_mode
 
-        # data = minio_client.get_object(image_url.split("/", 1)[0], image_url.split("/", 1)[1])
+    @staticmethod
-        # # data = s3.get_object(Bucket=image_url.split("/", 1)[0], Key=image_url.split("/", 1)[1])['Body']
+    def resize_and_crop(img, target_width, target_height):
-        #
+        # 获取原始图像的尺寸
-        # data_bytes = BytesIO(data.read())
+        original_height, original_width = img.shape[:2]
-        # image = Image.open(data_bytes)
-        # image_mode = image.mode
-        # # 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
-        # if image_mode == "RGBA":
-        #     # new_background = Image.new('RGB', image.size, (255, 255, 255))
-        #     # new_background.paste(image, mask=image.split()[3])
-        #     # image = new_background
-        #     return image, image_mode
-        # image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
-        # return image, "RGB"
 
-    # @staticmethod
+        # 计算目标尺寸的宽高比
-    # def read_image(image_url):
+        target_ratio = target_width / target_height
-    #     response = requests.get(image_url)
+
-    #     image_data = np.frombuffer(response.content, np.uint8)
+        # 计算原始图像的宽高比
-    #
+        original_ratio = original_width / original_height
-    #     # 解码图像
+
-    #     image = cv2.imdecode(image_data, 3)
+        # 调整尺寸
-    #     return image
+        if original_ratio > target_ratio:
+            # 原始图像更宽，按高度resize，然后裁剪宽度
+            new_height = target_height
+            new_width = int(original_width * (target_height / original_height))
+            resized_img = cv2.resize(img, (new_width, new_height))
+            # 裁剪宽度
+            start_x = (new_width - target_width) // 2
+            cropped_img = resized_img[:, start_x:start_x + target_width]
+        else:
+            # 原始图像更高，按宽度resize，然后裁剪高度
+            new_width = target_width
+            new_height = int(original_height * (target_width / original_width))
+            resized_img = cv2.resize(img, (new_width, new_height))
+            # 裁剪高度
+            start_y = (new_height - target_height) // 2
+            cropped_img = resized_img[start_y:start_y + target_height, :]
+
+        return cropped_img

app/service/utils/oss_client.py

@@ -63,7 +63,7 @@ if __name__ == '__main__':
     # url = "aida-users/87/print/956614a2-7e75-4fbe-9ed0-c1831e37a2c9-4-87.png"
     # url = "aida-users/89/single_logo/123-89.png"
     # url = "aida-users/89/product_image/string-89.png"
-    url = 'aida-users/89/relight_image/123-89.png'
+    url = "aida-results/result_c6520ce7-33a1-11ef-a8d3-b0dcefbff887.png"
     read_type = "PIL"
     if read_type == "cv2":
         img = oss_get_image(bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type)