🎉 Add: labelme to YOLOv5

README.md

@@ -1,3 +1,51 @@
+# How to use?
+
+### labelme2YOLOv5.py
+
+```shell
+Parent
+└── datasets
+    ├── MakeData
+    │   ├── README.md
+    │   ├── checkData.py
+    │   ├── labelme2YOLOv5.py
+    │   └── saveData.py
+    └── tmp
+        ├── data1.jpeg
+        ├── data1.json
+        ├── ...
+```
+
+```python
+Parent/datasets/MakeData$ python labelme2YOLOv5.py
+100%|█████████████████████████████████████████████| 5/5 [00:00<00:00,  9.03it/s]
+==============================
+No. Total Data:  5
+==============================
+Training Data: No. Images 3
+Training Data: No. GT 3
+Validation Data: No. Images 2
+Validation Data: No. GT 2
+==============================
+No. Total Image Data:  5
+No. Total GT Data:  5
+==============================
+```
+
+> Result
+
+```shell
+labelme
+├── images
+│   ├── train
+│   └── val
+└── labels
+    ├── train
+    └── val
+```
+
+### saveData.py
+
 ```shell
 Parent
 └── datasets
@@ -17,10 +65,6 @@ Parent
         └── saveData.py
 ```
 
-# How to use?
-
-### saveData.py
-
 ```shell
 Parent/datasets/MakeData$ python saveData.py
 100%|████████████████████████████████████████████████████████████████████████| 2235/2235 [00:45<00:00, 49.47it/s]

labelme2YOLOv5.py

@@ -0,0 +1,99 @@
+import os
+import shutil
+
+import csv
+import json
+
+from tqdm import tqdm
+import cv2
+
+
+def initializeData(DataStoreName):
+    tmp = os.getcwd()
+    if DataStoreName in os.listdir():
+        shutil.rmtree(DataStoreName)
+    os.mkdir(DataStoreName)
+    os.chdir(DataStoreName)
+    os.mkdir('images')
+    os.chdir('images')
+    os.mkdir('train')
+    os.mkdir('val')
+    os.chdir('..')
+    os.mkdir('labels')
+    os.chdir('labels')
+    os.mkdir('train')
+    os.mkdir('val')
+    os.chdir(tmp)
+
+def labelme2YOLOv5(target, relJson):
+    targetDirImg = DataStoreDir + '/images/' + target
+    targetDirLab = DataStoreDir + '/labels/' + target
+    relImage = relJson.replace('.json', '.jpeg')
+    # Make Target Data: IMG
+    shutil.copy(relImage, targetDirImg + '/' + relImage)
+    # Make Target Data: Poly (GT)
+    h, w, _ = cv2.imread(relImage).shape
+    with open(relJson) as f:
+        data = json.load(f)
+    tmp = data['shapes'][0]['points']
+    tar = []
+    cnt = 0
+    for j in tmp:
+        for k in j:
+            if cnt % 2 == 0:
+                tar.append(k/w)
+            else:
+                tar.append(k/h)
+    with open(targetDirLab + '/' + relJson.replace('.json', '.txt'), 'a', encoding='utf-8') as f:
+        wr = csv.writer(f, delimiter=' ')
+        wr.writerow([0, *tar])
+
+if __name__ == "__main__":
+    DataStoreName = "labelme"
+    os.chdir('..')
+    initializeData(DataStoreName)
+
+    datasets = os.getcwd()
+    DataStoreDir = datasets + '/' + DataStoreName
+
+    os.chdir('tmp')
+
+    candidate = []
+    for i in os.listdir():
+        if '.json' in i:
+            candidate.append(i)
+
+    cnt = 0
+    for c in tqdm(candidate):
+        if cnt % 3 == 0:
+            labelme2YOLOv5('val', c)
+        else:
+            labelme2YOLOv5('train', c)
+        cnt += 1
+
+    print('=' * 30)
+    print('No. Total Data: ', cnt)
+    print('=' * 30)
+
+    os.chdir(DataStoreDir + '/images/train')
+    tin = len(os.listdir())
+    print('Training Data: No. Images', tin)
+
+    os.chdir(DataStoreDir + '/labels/train')
+    ttn = len(os.listdir())
+    print('Training Data: No. GT', ttn)
+
+    os.chdir(DataStoreDir + '/images/val')
+    vin = len(os.listdir())
+    print('Validation Data: No. Images', vin)
+
+    os.chdir(DataStoreDir + '/labels/val')
+    vtn = len(os.listdir())
+    print('Validation Data: No. GT', vtn)
+
+    print('=' * 30)
+    print('No. Total Image Data: ', tin + vin)
+    print('No. Total GT Data: ', ttn + vtn)
+    print('=' * 30)
+
+    os.chdir(datasets + '/MakeData')