Machine Learning Android Image Classification App for Produce!

• Utilized Python, TensorFlow, Keras, OpenCV, Numpy, and Kotlin.
• Dataset consisting of 29k images from 28 different classifications of healthy and rotten produce items from Kaggle.
• Fine-tuned ResNet-50 CNN model built and trained in produce-tf.ipynb.
• Model attained a sparse categorical accuracy of 96.3%.

Results

Healthy Examples	Rotten Examples