/Capstone-ProdRecognition

Capstone project - product recognition

Primary LanguageJupyter Notebook

Capstone project: Product Recognition App

This project is an image classification application using Convolutional Neural Network, where trained model is saved as H5 file. Train images are manually scraped from an e-commerce website (Candian Tire) using Beautiful Soup and Selenium.

Required Libraries:

  1. streamlit
  2. skimage
  3. opencv
  4. tensorflow
  5. numpy
  6. pandas

To run in your local:

  1. Clone the project.
  2. Install the required libraries
  3. Run streamlit in your cmd or conda using this command: streamlit run prod_recog2.py
    **Note: ensure that you are inside the /app_codes directory when you run this command.
  4. Webpage will automatically open in your browser. If not, manually type this in the address box: http://localhost:8501/
  5. To edit the code, open prod_recog2.py in your python IDE or Notepad++