Improved mask conversion script

Signed-off-by: Jiri Podivin <jpodivin@gmail.com>

utils/convert_masks.py

@@ -1,5 +1,8 @@
 #!/bin/env python
 
+# Mask conversion for plantorgans
+# 2024 by Jiri Podivin
+
 import numpy as np
 import json
 import os
@@ -13,6 +16,8 @@ import os
 import tempfile
 import argparse
 import glob
+import shutil
+import tarfile
 
 class InputStream:
     def __init__(self, data):
@@ -174,25 +179,46 @@ def merge_masks(mask_metadata, target_mask_dir, label2id):
 
 def main():
     parser = argparse.ArgumentParser('maskconvert')
-    parser.add_argument('dataset_root')
+    parser.add_argument('dataset_root', help="Root directory of the dataset repo.")
 
     arguments = parser.parse_args()
-    annotations_folder_path = os.path.join(arguments.dataset_root, 'labels_raw')
-    tmp_mask_path = tempfile.mkdtemp('masks')
+
+    # Unzip raw labels to temporary location
+    tmp_raw_label_pth = tempfile.mkdtemp('_labels_raw')
+    with tarfile.open(os.path.join(arguments.dataset_root, 'labels_raw.tar.gz'), mode='r:gz') as archive:
+        archive.extractall(tmp_raw_label_pth)
+
+    annotations_folder_path = os.path.join(tmp_raw_label_pth, 'labels_raw')
+    
+    tmp_mask_path = tempfile.mkdtemp('_masks')
  
     files_to_process = glob.glob(f"{annotations_folder_path}/*")
 
-    # For sanity check
-    source_files = [os.path.basename(name) for name in glob.glob(f"sourcedata/**/*.jpg")]
+    # Image name -> path dict
+    images = {os.path.basename(x): x for x in glob.glob('sourcedata/**/*.jpg')}
+
+    # Image names
+    source_files = [k for k in images.keys()]
 
     metadata = pd.DataFrame(process_files_in_parallel(files_to_process, tmp_mask_path, source_files))
 
+    # Label map order IS important
     id2label = {int(k): v for k, v in enumerate(['void', 'Fruit', 'Leaf', 'Flower', 'Stem'])}
 
     label2id = {v: k for k, v in id2label.items()}
 
     result = merge_masks(metadata, os.path.join(arguments.dataset_root, 'semantic_masks'), label2id)
+
     result = pd.DataFrame(result).drop_duplicates()
+    
+    # Moving newly labeled images to right dir
+    images = {os.path.basename(x): x for x in glob.glob('sourcedata/**/*.jpg')}
+
+    for img in metadata['image']:
+        if 'unlabeled' in images[img]:
+            print("Moving {img} to labeled!")
+            shutil.move(images[img], os.path.join('sourcedata/labeled/', img))
+
     result.to_csv(
         os.path.join(arguments.dataset_root, 'semantic_metadata.csv'),
         index=False)