Florance

Florance is an intelligent deep learning tool that accurately classifies flowers—such as Rose, Sunflower, and Tulip—directly from images. It supports both real-time and batch predictions via a user-friendly console and Streamlit interfaces, enabling seamless and efficient flower identification for hobbyists and researchers alike.

Features

• Flower classification from user-provided images.
• Batch categorization of high-quality images for improved model performance.

Usage

All required libraries can be installed using a single-line command:

pip install -r requirements.txt

While to run the code:

Console-based version:

python main.py

Streamlit-based version:

streamlit run app.py

Description of various files:

• Analyzer.h5: Pretrained model trained using TeachableMachines for flower classification. For now, the model is only trained to recognize 3 flowers i.e. Rose, Sunflower, and Tulips
• app.py: Contains a streamlit-based version of the main code.
• flower_sort.py: Simply differentiate between clear images that are accurate for analysis from the once that are pixalated/blur.
• labels.txt: Contains the labels for the flower categories.
• main.py: Recognizes flowers from the provided image.
• requirements.txt: File containing all required Python modules.