Update README.md

README.md

@@ -90,7 +90,7 @@ There are three possibilities to train TrackR-CNN on APPLE_MOTS:
     - locate "load init" to your `models` folder, e.g. `"load_init": "/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/models/converted"`
     - locate "KITTI_segtrack_data_dir" to your `train` folder e.g. `"/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/data/APPLE_MOTS/train/"`
     - Set your batch size e.g. `"batch_size": 4`
-    - Set number of epoochs e.g. `"num_epochs": 4`
+    - Set number of epochs e.g. `"num_epochs": 4`
 - run `python main.py configs/A_CONFIG_FILE`
 
 2. Train APPLE_MOTS from KITTI MOTS checkpoint (fine-tuned on KITTI MOTS and pretrained on COCO and Mapillary) 
@@ -99,13 +99,13 @@ There are three possibilities to train TrackR-CNN on APPLE_MOTS:
     - locate "load init" to your `models` folder, e.g. `"load_init": "/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/models/conv3d_sep2/conv3d_sep2-00000005"`
     - locate "KITTI_segtrack_data_dir" to your `train` folder e.g. `"/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/data/APPLE_MOTS/train/"`
     - Set your batch size e.g. `"batch_size": 4`
-    - Set number of epoochs e.g. `"num_epochs": 4`
+    - Set number of epochs e.g. `"num_epochs": 4`
 - run `python main.py configs/A_CONFIG_FILE`
 
 3. Train APPLE_MOTS on e.g. `3dconv8_24` by using more epochs (in this case 1 epoch more):
 - Change in a config file:
     - locate "load init" to your `models` folder, e.g. `"load_init": "/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/models/3dconv8_24/3dconv8_24-00000003"`
-    - Set number of epoochs `"num_epochs": 4` should be higher than 3dconv8_24-0000000**3** otherwise it doesn't train
+    - Set number of epochs `"num_epochs": 4` should be higher than 3dconv8_24-0000000**3** otherwise it doesn't train
     - locate "KITTI_segtrack_data_dir" to your `train` folder e.g. `"/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/data/APPLE_MOTS/train/"`
 - run `python main.py configs/A_CONFIG_FILE`
 ### Custom dataset
@@ -117,7 +117,7 @@ There are three possibilities to train TrackR-CNN on APPLE_MOTS:
         - Option 2 `"load_init": "/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/models/converted"` 
     - locate "KITTI_segtrack_data_dir" to your `train` folder e.g. `"/home/saidlab/Thesis_Stefan_de_Jong/rt-obj-tracking/algorithms/TrackR-CNN/data/APPLE_MOTS/train/"`
     - Set your batch size e.g. `"batch_size": 4`
-    - Set number of epoochs e.g. `"num_epochs": 6`
+    - Set number of epochs e.g. `"num_epochs": 6`
     - Set `"input_size_train"`  and `"input_size_val"` to right resolutions. 
 - Calculate maximum number of detections in your dataset
     - Go to home folder e.g. (`cd rt-obj-tracking`)