Beer Price Checker
Take a photo, find the best price at a grocer near you.
- Beer Price Checker
- Streamlit server hosted on Google Cloud Platform VM. Should be running until June 30, 2021.
Objective
- To find the best price for a beer you wish to purchase at a grocer near you.
Project Overview
- Scraped over 3500+ images for 18 brands of beer.
- Cropped images to train Convolutional Neural Network
- Identifed beer brands with high accuracy and provided best price for purchase
Code and Resources
Python Version: Python 3.7.10 (Google Colab)
Tensorflow 2.4.1
Opencv-python 4.1.2
Inbac 2.1.0
Packages: pandas, numpy, matplotlib, seaborn, selenium,
Teammates: Alex Li’s GitHub & lhwj0619’s GitHub
Web Scraping
- Initially started with manual scraping of beer logo images to test the viability of the image recognition project.
- After some promising results from the CNN, we used some template python codes to scrape images off Google Search.
- Selenium was used to scrape the price information from https://online-price-watch.consumer.org.hk/opw/search/asahi
Data Cleaning
- The data from Consumer Council was placed in a pandas DataFrame. Had to remove minor data figures for formatting.
- Images were cropped using a standalone python .exe called inbac.
- Labels were applied to the images using folders.
Modelling
- The baseline CCN model was taken from https://www.tensorflow.org/tutorials/images/classification.
- Validation accuracy improved significantly when dropout layers were added to the model.
Baseline Model
model = tf.keras.Sequential([
layers.experimental.preprocessing.Rescaling(1./255),
#layers.Conv2D(input_shape=(img_height,img_width,3),filters=64,kernel_size=(2,2),padding="same", activation="relu"),
layers.Conv2D(64, 3, activation='relu'),
layers.Conv2D(64, 2, activation='relu'),
layers.MaxPooling2D(),
layers.Conv2D(128, 2, activation='relu'),
layers.Conv2D(128, 2, activation='relu'),
layers.MaxPooling2D(),
layers.Dropout(0.2),
layers.Conv2D(32, 3, activation='relu'),
layers.MaxPooling2D(),
layers.Flatten(),
layers.Dense(128, activation='relu'),
layers.Dense(num_classes, activation='softmax')
])
Final Model
model = tf.keras.Sequential([data_augmentation])
model.add(Conv2D(input_shape=(img_height,img_width,3),filters=64,kernel_size=(3,3),padding="same", activation="relu", kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(MaxPooling2D(pool_size=2,))
model.add(Dropout(0.2))
model.add(Conv2D(kernel_size = 2, filters = 64, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(Conv2D(kernel_size = 2, filters = 64, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(MaxPooling2D(pool_size=2))
model.add(Dropout(0.2))
model.add(Conv2D(kernel_size = 2, filters = 128, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(Conv2D(kernel_size = 2, filters = 128, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(MaxPooling2D(pool_size=2))
model.add(Dropout(0.2))
model.add(Conv2D(kernel_size = 2, filters = 256, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(Conv2D(kernel_size = 2, filters = 256, activation='relu', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
model.add(MaxPooling2D(pool_size = 2))
model.add(Dropout(0.2))
model.add(GlobalMaxPooling2D())
#model.add(GlobalAveragePooling2D())
model.add(Dense(num_classes, activation = 'softmax', kernel_regularizer=regularizers.l1_l2(l1=1e-5, l2=1e-4)))
Production
- Streamlit was used to deploy the model.
Presentation
Futher Improvements
- More image data to increase accuracy
- Implement ensemble methods to increase accuracy further
- Deploy model in a mobile app
- Expand the beer brand selection
- Expand into other grocery categories such as bottled seasoning, packaged foods, canned foods, etc
- Expand pricing of goods database
Business Value
- Collect data on items that are price sensitive
- Opportunities for grocers to market directly to the consumer
- Logistic companies can offer consolidated grocery services