update README w/ instructions on siamese training

README.md

@@ -29,7 +29,14 @@ Please notice that we use only 32 frames per video. You can tweak easily tweak t
 
 ### Train
 In [train_all.sh](scripts/train_all.sh) you can find a comprehensive list of all the commands for training the models presented in the paper. 
-Please refer to the comments into the script for hints on their usage.
+Please refer to the comments into the script for hints on their usage. 
+
+#### Training models singularly
+If you want to train some models without referring to the script:
+- for the **non-siamese** architectures (e.g. EfficientNetB4, EfficientNetB4Att), you can simply specify the model in [train_binclass.py](train_binclass.py) as the *--net* parameter;
+- for the **siamese** architectures (e.g. EfficientNetB4ST, EfficientNetB4AttST), you have to:
+  1. train the architecture as a feature extractor first, using the [train_triplet.py](train_triplet.py) script and being careful of specifying its name in the *--net* parameter **without** the ST suffix. For instance, for training the EfficientNetB4ST you will have to first run `python train_triplet.py --net EfficientNetB4 --otherparams`;
+  2. finetune the model using [train_binclass.py](train_binclass.py), being careful this time to specify the architecture's name **with** the ST suffix and to insert as the *--init* argument the path to the weights of the feature extractor trained at the previous step. You will end up running something like `python train_binclass.py --net EfficientNetB4ST --init path/to/EfficientNetB4/weights/trained/with/train_triplet/weights.pth --otherparams`
 
 ### Test 
 In [test_all.sh](scripts/test_all.sh) you can find a comprehensive list of all the commands for testing the models presented in the paper. 
@@ -53,8 +60,8 @@ Additionally, you can find notebooks for results computations in the [notebook](
 
 ## Credits
 [Image and Sound Processing Lab - Politecnico di Milano](http://ispl.deib.polimi.it/)
-- Nicolò Bonettini
-- Edoardo Daniele Cannas
-- Sara Mandelli
-- Luca Bondi
-- Paolo Bestagini
+- Nicolò Bonettini (nicolo.bonettini@polimi.it)
+- Edoardo Daniele Cannas (edoardodaniele.cannas@polimi.it)
+- Sara Mandelli (sara.mandelli@polimi.it)
+- Luca Bondi (luca.bondi@polimi.it)
+- Paolo Bestagini (paolo.bestagini@polimi.it)