IFFSE

Instagram Facial Feature Search Engine

Setup

The recommended way of installing a local copy of facemaps is to use a python 3.6 conda environment:

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O conda.sh
chmod +x conda.sh
bash conda.sh
source ~/.bashrc # or `source ~/.zshrc` if you're using zsh

# Create new conda env and use it
conda create -n facemaps python=3.6 anaconda
source activate facemaps

# Annoy Issue:
# Annoy uses libstdc++, Anaconda provides its own libstdc++,
# to use annoy in Anaconda, run:
cp /usr/lib/x86_64-linux-gnu/libstdc++.so.6 $CONDA_PATH/envs/facemaps/lib 

Dependencies:

conda install -c conda-forge dlib=19.4
conda install pytorch torchvision -c soumith
pip install -r requirements.txt

Deploying a local copy

1. Before anything, you'll need to download a copy of the pretrained weights:

git clone https://github.com/kendricktan/iffse.git
cd iffse
mkdir pretrained_weights
wget https://github.com/ageitgey/face_recognition_models/raw/master/face_recognition_models/models/shape_predictor_68_face_landmarks.dat -O ./pretrained_weights/shape_predictor_68_face_landmarks.dat
wget https://www.dropbox.com/s/lhus56cn1xikzeb/openface_cpu.pth?dl=1 -O ./pretrained_weights/openface_cpu.pth

2. Time to scrap some data! I've written async multi-threaded scrapper that doesn't require any instagram credentials :-). The following tags are used int scrapper.py, change them to whatever tags you want to scrap (e.g. #NYC, #gymlife)

# What kind of tags do we want to scrap
tags_to_be_scraped = [
    'selfie', 'selfportait', 'dailylook', 'selfiesunday',
    'selfietime', 'instaselfie', 'shamelessselefie',
    'faceoftheday', 'me', 'selfieoftheday', 'instame',
    'selfiestick', 'selfies'
]

2. Run python scrapper.py and wait for a few hours / days. Ideally you do this step on a C4 instance on AWS as it'll max out your cores.

3. Run server

# If you're running it for the first time
# or want to update search indexes
python app.py --rebuild-tree

# Otherwise
python app.py

Special thanks:

OpenFacePytorch - OpenFace's nn4.small2.v1.t7 model in PyTorch