not done yet.

.gitignore

@@ -0,0 +1 @@
+icdar2015_aliocr/

aliocr_IC15_convert.py

@@ -4,8 +4,7 @@
 
 """
 
-给 PaddleOCR 用，前面是坐标和图片都变换；这里图像不变，坐标不变 
-
+给 DBNet 官方代码用
 
 将阿里OCR 的识别结果（图片和标注）转换成 icdar2015 格式 (注意：它的文本是含 utf8 bom 的)
 
@@ -133,8 +132,8 @@ def cutPoly(img, pts):
 if __name__ == "__main__":
 
     # 验证原版的文本标记框
-    im = './train_images/img_1.jpg'
-    gt = './train_gts/gt_img_1.txt'
+    im = './datasets/icdar2015/train_images/img_1.jpg'
+    gt = './datasets/icdar2015/train_gts/gt_img_1.txt'
 
     # 验证自已生成的标记框
     # im = './icdar2015_aliocr/imgs/training/img_1.jpg'
@@ -187,12 +186,14 @@ if __name__ == "__main__":
 
         #cv2.imwrite("poly.jpg", img)
 
-        # cv2.imshow("poly", img)
-        # cv2.waitKey()
+        cv2.imshow("poly", img)
+        cv2.waitKey()
 
     # 开始转换
 
     out_dir = 'icdar2015_aliocr'
+    # train_list.txt
+    # test_list.txt
 
     # https://help.aliyun.com/document_detail/294540.html 阿里云ocr结果字段定义
     # prism-wordsInfo 里的 angle 文字块的角度，这个角度只影响width和height，当角度为-90、90、-270、270，width和height的值需要自行互换
@@ -201,7 +202,10 @@ if __name__ == "__main__":
     dir_img = './data/img'  # '/yingedu/www/ocr_server/data/img'
 
     train_list = []
-    train_list_txt_path = os.path.join(out_dir, 'train_list.txt')
+    train_list_path = os.path.join(out_dir, 'train_list.txt')
+
+    test_list = []
+    test_list_path = os.path.join(out_dir, 'test_list.txt')
 
     g_count = 1
 
@@ -224,8 +228,8 @@ if __name__ == "__main__":
             imgdata = np.frombuffer(imgdata, np.uint8)
             img = cv2.imdecode(imgdata, cv2.IMREAD_UNCHANGED)
 
-            # cv2.imshow('img', img)
-            # cv2.waitKey(0)
+            cv2.imshow('img', img)
+            cv2.waitKey(0)
 
         if len(img.shape) != 3:  # 转彩图
             img_color = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
@@ -239,21 +243,36 @@ if __name__ == "__main__":
 
 
         # 生成1000 张一模一样的图
-        for i in range(1, 1000+1):
+        for i in range(1, 2): # 1000+1
 
             num_img = i
 
-            img_name = "img_{}.jpg".format(num_img)
-            gt_name = "gt_img_{}.txt".format(num_img)
+            img_name = "img_{:06d}.jpg".format(num_img)
+            gt_name = "gt_img_{:06d}.txt".format(num_img)
+
+            is_train_img = random.choices([0, 1], weights=[0.15, 0.85])[0]
+                # 85% 的概率是训练图
 
             gt_txt_list = []
 
-            train_list.append(img_name)
+            if is_train_img:
+                train_list.append(img_name)
+            else:
+                test_list.append(img_name)
             # num_img += 1
 
-            img_path = os.path.join(out_dir, 'imgs', 'training', img_name)
+            img_path = os.path.join(out_dir, 'train_images', img_name)
             img_gt_path = os.path.join(
-                out_dir, 'annotations', 'training', gt_name)
+                out_dir, 'train_gts', gt_name)
+            
+            dir1 = os.path.dirname(img_path)
+            dir2 = os.path.dirname(img_gt_path)
+
+            if not os.path.exists(dir1):
+                 os.makedirs(dir1)
+
+            if not os.path.exists(dir2):
+                 os.makedirs(dir2)
 
             cv2.imwrite(img_path, img)
 
@@ -277,11 +296,10 @@ if __name__ == "__main__":
                 elif angle != 0:
 
                     # 变换前画出绿框，方便追踪点的前后变化
-                    # img_color = cv2.rectangle(img_color, (word_x, word_y), (
-                    #     word_x + word_width, word_y + word_height), (0, 255, 0), 2)  # 矩形的左上角, 矩形的右下角
+                    img_color = cv2.rectangle(img_color, (word_x, word_y), (word_x + word_width, word_y + word_height), (0, 255, 0), 2)  # 矩形的左上角, 矩形的右下角
 
-                    # cv2.imshow("green", img_color)
-                    # cv2.waitKey(0)
+                    cv2.imshow("green", img_color)
+                    cv2.waitKey(0)
 
                     # 变换前的多边形蓝框
                     points = np.array([
@@ -291,12 +309,12 @@ if __name__ == "__main__":
                         [word_x, word_y + word_height],                # 左下
                     ])
 
-                    # # cv2.fillPoly(img_color, pts=[points], color=(255, 0, 0)) # 填充
-                    # cv2.polylines(img_color, [points], isClosed=True, color=(
-                    #     255, 0, 0), thickness=1)  # 只画线，不填充
+                    # cv2.fillPoly(img_color, pts=[points], color=(255, 0, 0)) # 填充
+                    cv2.polylines(img_color, [points], isClosed=True, color=(
+                        255, 0, 0), thickness=1)  # 只画线，不填充
 
-                    # cv2.imshow("polys", img_color)
-                    # cv2.waitKey(0)
+                    cv2.imshow("polys", img_color)
+                    cv2.waitKey(0)
 
                     # 获取图像的��度，并计算中心
                     (h, w) = img_color.shape[:2]
@@ -310,8 +328,8 @@ if __name__ == "__main__":
                     img_color = cv2.warpAffine(img_color, M, (w, h))
                     img_color_transform = img_color.copy()
 
-                    # cv2.imshow("after trans", img_color)
-                    # cv2.waitKey(0)
+                    cv2.imshow("after trans", img_color)
+                    cv2.waitKey(0)
 
                     # https://docs.opencv.org/2.4/doc/tutorials/imgproc/imgtrans/warp_affine/warp_affine.html  # 原理
                     # https://stackoverflow.com/questions/30327659/how-can-i-remap-a-point-after-an-image-rotation # How can I remap a point after an image rotation?
@@ -345,8 +363,8 @@ if __name__ == "__main__":
 
                     
 
-                    # cv2.imshow("orgin", img_color_origin)
-                    # cv2.waitKey(0)
+                    cv2.imshow("orgin", img_color_origin)
+                    cv2.waitKey(0)
 
 
 
@@ -364,8 +382,8 @@ if __name__ == "__main__":
                 rd = [pos[2]['x'], pos[2]['y']]
                 ld = [pos[3]['x'], pos[3]['y']]
 
-                # 生成 icdar2015 格式的人工标记训练数据（用于训练 mmocr）
-                #gt_txt_list.append( "{},{},{},{},{},{},{},{},{}".format(lu[0], lu[1], ru[0], ru[1], rd[0], rd[1], ld[0], ld[1], word) )
+                # 生成 icdar2015 格式的人工标记训练数据（用于训练官方DB）
+                gt_txt_list.append( "{},{},{},{},{},{},{},{},{}".format(lu[0], lu[1], ru[0], ru[1], rd[0], rd[1], ld[0], ld[1], word) )
 
                 # 绘制矩形
                 start_point = (x, y)  # 矩形的左上角
@@ -377,10 +395,10 @@ if __name__ == "__main__":
                 thickness = 2
 
                 # 逐行画框
-                # img_color = cv2.rectangle(img_color, start_point, end_point, color, thickness)
-                # cv2.imshow("box", img_color)
+                img_color = cv2.rectangle(img_color, start_point, end_point, color, thickness)
+                cv2.imshow("box", img_color)
 
-                # cv2.waitKey(0)
+                cv2.waitKey(0)
 
                 points = [ lu, ru, rd, ld ]