Feature/contrastive loss

.gitignore

@@ -1,6 +1,11 @@
 #ide
 .idea/
 
+# Data
+output_dir/
+datasets/
+
+
 # checkpoints
 experiments/
 

bin_mean_shift.py

@@ -117,7 +117,7 @@ def merge_center(self, seed_point, bandwidth=0.25):
 
         # merge center if distance between two points less than bandwidth
         sorted_intensity, indices = torch.sort(intensity, descending=True)
-        is_center = np.ones(n, dtype=np.bool)
+        is_center = np.ones(n, dtype=bool)
         indices = indices.cpu().numpy()
         center = np.zeros(n, dtype=np.uint8)
 

configs/config.yaml

@@ -1,21 +1,23 @@
 seed: 123
 num_gpus: 1
-num_epochs: 100
-resume_dir: None
+num_epochs: 5
+resume_dir: /Users/dimafadeev/Desktop/Catalog/TUM/WS23/ML3D/repo/output/models/
 print_interval: 10
 
+
 solver:
   method: adam
   lr: 0.0001
   weight_decay: 0.00001
 
 dataset:
-  root_dir: /new_disk2/yuzh/PlaneNetData/
+  root_dir: /Users/dimafadeev/Desktop/Catalog/TUM/WS23/ML3D/repo/output/processed/
   batch_size: 16
   num_workers: 8
 
 model:
-  arch: resnet101
+  arch: resnet101 #  dpt #  
   pretrained: True
   embed_dims: 2
   fix_bn: False
+  semantic: True

data_tools/RecordReaderAll.py

@@ -1,5 +1,6 @@
 # modified from https://github.com/art-programmer/PlaneNet
-import tensorflow as tf
+import tensorflow.compat.v1 as tf
+tf.disable_v2_behavior()
 
 HEIGHT=192
 WIDTH=256

data_tools/convert_tfrecords.py

@@ -1,11 +1,13 @@
-import tensorflow as tf
 import numpy as np
 import os
 import argparse
 
 from RecordReaderAll import *
 
-os.environ['CUDA_VISIBLE_DEVICES']=''
+import tensorflow.compat.v1 as tf
+tf.disable_v2_behavior()
+
+#os.environ['CUDA_VISIBLE_DEVICES']='0'
 
 parser = argparse.ArgumentParser()
 parser.add_argument('--input_tfrecords_file', type=str,
@@ -27,14 +29,14 @@
     os.makedirs(output_dir)
 
 if data_type == 'train':
-    file_list = open(output_dir + '/train.txt', 'w')
     output_dir = os.path.join(output_dir, 'train')
-    os.makedirs(output_dir)
+    os.makedirs(output_dir,exist_ok=True)
+    file_list = open(output_dir + '/train.txt', 'w')
     max_num = 50000
 elif data_type == 'val':
-    file_list = open(output_dir + '/val.txt', 'w')
     output_dir = os.path.join(output_dir, 'val')
-    os.makedirs(output_dir)
+    os.makedirs(output_dir, exist_ok=True)
+    file_list = open(output_dir + '/val.txt', 'w')
     max_num = 760
 else:
     print("unsupported data type")
@@ -74,7 +76,7 @@
 
         file_list.write('%d.npz\n' % (i, ))
 
-        if i % 100 == 99: 
+        if i % 1000 == 99: 
             print(i)
 
 file_list.close()