From dbbad3dbec7e1f0b53bed4456c5cb44f97da27d4 Mon Sep 17 00:00:00 2001 From: Khairul Imam Date: Mon, 29 Jul 2019 09:04:55 +0800 Subject: [PATCH] Update README.md --- README.md | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index ada742f..ea01020 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,7 @@ # Facenet for face recognition using pytorch - Pytorch implementation of the paper: "FaceNet: A Unified Embedding for Face Recognition and Clustering". - Training of network is done using triplet loss. +- This work is modified in some functionality from the original work by [Taebong Moon](https://github.com/tbmoon/facenet) and then retrained for the purpose of completing my BS degree. The full report can be found at [Verifikasi Kemiripan Wajah Dengan _Deep Learning_ Menggunakan Arsitektur _Siamese_](https://github.com/khrlimam/skripsi/raw/master/pdfs/finishing.pdf) # How to train/validate model @@ -13,7 +14,7 @@ - Write list file of face images by running "datasets/write_csv_for_making_dataset.py" - `python write_csv_for_making_dataset.py --root-dir=/path/to/dataset/dir --final-file=dataset.csv` - - `datasets/write_csv_for_making_dataset.py` is multiprocess version of previous `.ipynb`. This way generating csv dataset is faster. + - `datasets/write_csv_for_making_dataset.py` is multiprocess version of previous `.ipynb`. This way generating csv dataset is much faster. - Train - Again, one need to modify paths in accordance with location of image dataset. @@ -32,7 +33,10 @@ - ROC curve on LFW datasets for validation -![roc curve](./log/tmp/roc_valid_epoch_39.png) +![roc curve](./log/tmp/roc.png) + +- Test the model on 25 pair of images +![Test Result on 25 pair of images](./log/tmp/test-result.png) # References