From 1858f7af8ae286995fc815946e6023f22b00d372 Mon Sep 17 00:00:00 2001 From: Edoardo Daniele Cannas Date: Sun, 26 Apr 2020 19:28:05 +0200 Subject: [PATCH] update README w/ instructions on siamese training --- README.md | 19 +++++++++++++------ 1 file changed, 13 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index acb3243..79c9fb1 100644 --- a/README.md +++ b/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 \ No newline at end of file +- 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)