Deep learning model trained via Clarifai on data scraped from Yuki's Tinder for automated swiping. Used CLarifai as a showcase of their platform. Probably will get better results with finetuning on top of FaceNet.
- Python versions 3.5.2 absl-py==0.2.2 applescript==0.0.1 astor==0.7.1 beautifulsoup4==4.6.3 cached-property==1.5.1 certifi==2018.10.15 chardet==3.0.4 clarifai==2.4.1 configparser==3.5.0 cycler==0.10.0 decorator==4.3.0 detect==0.0.2 future==0.17.1 gast==0.2.0 googleapis-common-protos==1.5.5 graphviz==0.8.4 grpcio==1.13.0 gspread==3.0.1 h5py==2.8.0 httplib2==0.11.3 idna==2.7 jsonschema==2.6.0 Keras==2.2.0 Keras-Applications==1.0.2 Keras-Preprocessing==1.0.1 kiwisolver==1.0.1 Markdown==2.6.11 matplotlib==2.2.2 numpy==1.14.5 oauth2client==4.1.3 only==1.0.3 opencv-python==3.4.3.18 pgrep==0.0.0 Pillow==5.3.0 playsound==1.2.2 protobuf==3.6.0 psutil==5.4.8 public==2.0.1 pyasn1==0.4.4 pyasn1-modules==0.2.2 PyAutoGUI==0.9.38 pydot==1.2.4 pygame==1.9.4 PyMsgBox==1.0.6 pynder==0.0.13 pyparsing==2.2.0 Pypubsub==4.0.0 PyScreeze==0.1.18 python-dateutil==2.7.3 pyttsx==1.1 pyttsx3==2.7 PyTweening==1.0.3 pytz==2018.5 pywin32==224 PyYAML==3.13 requests==2.20.0 robobrowser==0.5.3 rsa==4.0 runcmd==0.0.3 scikit-learn==0.19.2 scipy==1.1.0 six==1.11.0 temp==1.0.2 tensorboard==1.9.0 tensorflow==1.9.0 termcolor==1.1.0 urllib3==1.24 vlc==0.1.1 Werkzeug==0.14.1 wxPython==4.0.3
- Input images
- 5000 Tinder profile images "faces_of_tinder_profile" dataset from Kaggle
- Annotation
- The images were divided into two categories "right" and "left" based on Yuki's preferences.
- Login to Clarifai $ https://clarifai.com/developer/account/login
- Download Tinder profile images into a file.
- run FaceCropper.py in the folder to crop all the faces from the images.
- all the images of cropped faces would be saved in the same file location
- Annotate the cropped Tinder profile images to get data to start with
- Separate the faces into two different folders, “right” and “left”
- Split the annotated data into training and testing data.
- 80% training 20% testing was used
- Upload the training data on the Clarifai account
- make sure to upload both groups of images “right” and “left” separately
- Run Training.py
- make sure to type the api_key on line16
- change the train test split if necessary
- Login to PCver of Tinder $ https://tinder.com/app/recs
- Proceed further to the screen used to swipe left and right
- Run SwipuWaifu.py
- quickly change back to the browser so that the software can start swiping
WARNING: The Tinder account might be temporarily disabled/BANed when running scraper.py, as the server might detect rapid uncertain access from this strip of code. Run with your own risk.
- scraper.py can be used to scrape data (Tinder profile images) directly from Tinder
- Authenticate with the facebook account by inputing the login details in authenticate.py