Add train_test_indices file

train_test_indices.py

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+# In the future we might need to define exact train and test sets to compare different models. This script has initiated for this purpose.
+
+import os
+import cv2
+
+def load_images_from_folder(folder):
+    images = []
+    for filename in os.listdir(folder):
+        if filename.endswith(".png"):
+            img = cv2.imread(os.path.join(folder, filename))
+            if img is not None:
+                images.append(img)
+    return images
+root_folder = '/home/sabrina/stinkbugs/labeled-data/'
+
+directory_list = list()
+for root, dirs, files in os.walk("/home/sabrina/stinkbugs/labeled-data", topdown=False):
+    for name in dirs:
+        directory_list.append(os.path.join(root, name))
+
+folders = [os.path.join(root_folder, x) for x in directory_list]
+all_images = [img for folder in folders for img in load_images_from_folder(folder)]
+# %%
+n_frames = len(all_images)
+frames = list(range(0,n_frames))
+random.Random(4).shuffle(frames)
+split =  95
+percent = int(split * len(frames) / 100)
+train1 = frames[:percent]
+test1 = frames[percent:]
+
+list1 = deeplabcut.create_training_dataset(
+    config_path,
+    num_shuffles= suffle,
+    net_type="resnet_50",
+    augmenter_type="imgaug",
+    trainIndices = [train1],
+    testIndices = [test1],
+)