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Tony607 · Jul 27, 2019 · 8dde052 · 8dde052
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diff --git a/.gitignore b/.gitignore
@@ -2,4 +2,4 @@
 *.ipynb_checkpoints
 __pycache__
 .vscode/
-coco.json
+trainval.json
diff --git a/README.md b/README.md
@@ -1,10 +1,10 @@
-# [How to create custom COCO data set for instance segmentation]() | DLology blog
+# [How to create custom COCO data set for instance segmentation](https://www.dlology.com/blog/how-to-create-custom-coco-data-set-for-instance-segmentation/) | DLology blog
 
 ## Quick start
 
 Then you can run the `labelme2coco.py` script to generate a COCO data formatted JSON file for you.
 ```
-python labelme2coco.py labelme_images
+python labelme2coco.py images
 ```
 Then you can run the following Jupyter notebook to visualize the coco annotations. `COCO_Image_Viewer.ipynb`
 

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diff --git a/labelme2coco.py b/labelme2coco.py
@@ -2,7 +2,6 @@
 import argparse
 import json
 
-# import cv2
 from labelme import utils
 import numpy as np
 import glob
@@ -20,7 +19,6 @@ def __init__(self, labelme_json=[], save_json_path="./coco.json"):
         self.images = []
         self.categories = []
         self.annotations = []
-        # self.data_coco = {}
         self.label = []
         self.annID = 1
         self.height = 0
@@ -36,7 +34,7 @@ def data_transfer(self):
                 for shapes in data["shapes"]:
                     label = shapes["label"].split("_")
                     if label not in self.label:
-                        self.categories.append(self.categorie(label))
+                        self.categories.append(self.category(label))
                         self.label.append(label)
                     points = shapes["points"]
                     self.annotations.append(self.annotation(points, label, num))
@@ -57,12 +55,12 @@ def image(self, data, num):
 
         return image
 
-    def categorie(self, label):
-        categorie = {}
-        categorie["supercategory"] = label[0]
-        categorie["id"] = len(self.label) + 1
-        categorie["name"] = label[0]
-        return categorie
+    def category(self, label):
+        category = {}
+        category["supercategory"] = label[0]
+        category["id"] = len(self.label) + 1
+        category["name"] = label[0]
+        return category
 
     def annotation(self, points, label, num):
         annotation = {}
@@ -150,7 +148,9 @@ def save_json(self):
         help="Directory to labelme images and annotation json files.",
         type=str,
     )
-    parser.add_argument("--output", help="Output json file path.", default="coco.json")
+    parser.add_argument(
+        "--output", help="Output json file path.", default="trainval.json"
+    )
     args = parser.parse_args()
     labelme_json = glob.glob(os.path.join(args.labelme_images, "*.json"))
     labelme2coco(labelme_json, args.output)