Upload make_RGB_dataset.py

make_RGB_dataset.py

@@ -0,0 +1,88 @@
+'''
+1. Please first extract RGB folder in each video folder in each scene folder and organize as below:
+|-- RGB_file
+    |-- 1
+        |-- 1.1
+        ...
+        |-- 1.4
+        # (end of folder)
+    |
+    |-- 2
+        |-- 2.1
+            |-- color (folder)
+            #
+        |-- 2.2
+            |-- color
+            #
+        |-- 2.3
+            |-- color
+            #
+        |-- 2.4
+            |-- color
+            #
+        |-- 2.5
+            |-- color
+            #
+    |
+    ...
+    |
+    |-- 11
+        |-- 11.1
+        ...
+        |-- 11.5
+        #
+    |
+    #
+
+
+and run the code below
+'''
+import h5py
+import numpy as np
+import io
+from PIL import Image
+import os
+from tqdm import tqdm
+
+f = h5py.File("RGB_dataset.hdf5", "w")
+
+# saving path: f["color/scene/video/"]
+# color path: 
+color_file_path = "RGB_file"
+color_grp = f.require_group("color")
+
+for scene in tqdm(os.listdir(color_file_path)):
+    print(scene)
+    scene_file_path = os.path.join(color_file_path, scene)
+    scene_grp = color_grp.require_group(scene)
+    for video in tqdm(os.listdir(scene_file_path)):
+        if video=="groundtruth":
+            continue
+        video_grp = scene_grp.require_group(video)
+        video_color_path = os.path.join(scene_file_path,video,"color")
+        for image in tqdm(os.listdir(video_color_path)):
+            img_path = os.path.join(video_color_path, image)
+            with open(img_path, 'rb') as img_f:
+                binary_data = img_f.read()
+            binary_data_np = np.asarray(binary_data)
+            dset = video_grp.create_dataset(f'{image[:-4]}', data=binary_data_np)
+f.close()
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+