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Repo for storing files for the graduation project. It holds code for the CV and NLP Model

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Graduation Project Code - Changelog

Table of Contents

Week 11

Mar 25:

  • Restructured Saved Weights Folder
  • Added 6 Models trained on data of 13 words and 4 people
    • 5 FPS x2 (Max Accuracy and Min Loss)
    • 9 FPS x2 (Max Accuracy and Min Loss)
    • 13 FPS x2 (Max Accuracy and Min Loss)
  • Added Notebooks that were used for training and recording data

Mar 21:

  • Added 4 Models trained on data of 13 words and 3 people

    • 25 FPS x2 (Max Accuracy and Min Loss)
    • 13 FPS
    • 9 FPS
  • Added 2 Models trained on data of 13 words and 4 people

    • 25 FPS
    • 13 FPS

Week 10

Mar 19:

  • Alphabets added to NLP Dataset
  • Added new NLP Model and Weights trained on new dataset

Mar 15:

  • Added NLP weights to handle "Hello [Name]"

Mar 14:

  • Added 2 Models trained on data of 10 words and 4 people
  • Updated Script to Record CV Data - CV_Model.ipynb

Week 9

Mar 6:

  • Dataset changes
    • Combined 2 datasets (Dataset 1 and Dataset 2) into one dataset - Dataset_1780_rows.csv
    • Created a double version of the dataset
    • Fixed finger spelling placeholders
    • Added new sentences
  • Updated NLP Script
    • Handles finger spelling now
    • Adds '?' after 6 W's and How
    • Fixed hardcoded values when initialing model
  • Updated weights and myVars.txt for the NLP model

Week 8

Mar 5:

  • Updated NLP Script
    • Added function preprocess_sentence that will handle all preprocessing
    • Added code to handle finger spelling
    • Handling '?' (QM-wig) and manually adding ? to decoded sentence

Mar 3:

  • Computer Vision Data Collection script updated
    • Added code to prompt action on screen while collecting data
  • Uploaded the Updated version of Main Notebook - Updated.ipynb
  • Uploaded new models in Saved Weights folder

Mar 1:

  • Computer Vision data collection script changes
    • Removed useless Imports
    • Changed draw_landmarks (Face landmarks)
    • Added function (extract_keypoints)
    • Changed sequence length to 25 and number of sequences to 40

Feb 28:

  • Added 2 new datasets for NLP

Week 7

Feb 22:

  • Uploaded 4 new models with training Camera position as Standing and Seated
  • Updated NLP_Model.py so that it handles words that aren't part of the dictionary

Feb 21:

  • Created new issues and assigned who needs to work on them
  • Removed all additional Datasets

Week 5

Feb 12:

  • Added the Computer Vision Model folder

    • With Notebooks folder containing the main notebook and the saved weights
    • With Scripts folder containing 3 scripts for training data collection
  • Restructured the NLP Model folder

    • Reduced the folder hierarchy for better easy navigation
    • Added a ReadMe file

Feb 11:

  • Restructured the repository
  • Added 2 Main folders for each Model; NLP Model and Computer Vision Model.

Feb 10:

  • Added ReadMe file and small update to NLP_Model.py
    • ReadMe file for the Scripts/Model directory that shows how to use the NLP Model
    • NLP_Model.py now has a loop that keeps taking input

Feb 8:

  • Major update to NLP_Model.py
    • Combined generate_batch function with decode_sequence and now it takes an user input instead of a dataset
    • Made it so that the python program can take an argument, this will be the ASL text
    • Removed unused imports
    • Added new colors for printing text
    • Removed code for importing and preprocessing dataset
    • Removing import to other file with functions, only 1 function was being used so it has now been moved to the file itself (read_list_from_file)
    • Added timing for all sections of the code
    • Removed all unnecessary code

Feb 6:

  • Added a script for NLP model
    • Reorganized Scripts folder into 2 parts; Data & Model
      • Scripts/Data holds all the scripts related to data extraction
      • Scripts/Model holds the python code for the NLP model
    • Updated Encoder_Decoder_V4 file to save model in H4 format
    • Added Scripts/Model folder
      • NLP_Model.py: Refactored the python notebook code
      • functions.py: Unimportant functions moved to this
      • myVars.txt: Dependant variables that take the longest time to load are now saved in here (over a pkl file for readability)
      • Incomplete task: Change the decoder function code to take user inputs

Week 4

Feb 5:

  • Added Encoder_Decoder V4
    • Removed .pkl files as they are not required (check commit description for more details)
    • Added a file with the dataset rows doubled for testing

Week 3

Jan 25:

Jan 23:

  • Dataset changes
    • Removing all maths sentences
    • Some sentences had 3 lines (removing those sentences)
  • Fix for removingSpacesFromDataset.py: Previous code wasn't iterating properly and was pasting the same sentences twice
  • Reorganized repository

Jan 22: Added Encoder_Decoder_V2.ipynb: 2nd Version of EncoderDecoder

Jan 20: New dataset added, has around 2K rows of data & script written by her

Week 2

Jan 19: Updated python notebook with completed encoder-decoder code. Still needs a lot of improvements

Jan 17: Repo set up

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Repo for storing files for the graduation project. It holds code for the CV and NLP Model

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