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Flower-Recognizer is a deep learning model that classifies flower images, specifically recognizing Rose, Sunflower, and Tulip. It allows users to upload images for real-time classification and offers batch processing for enhanced performance.

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Flower-Recognizer

A deep learning model designed to classify flowers such as Rose, Sunflower, and Tulip using image inputs.

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.

About

Flower-Recognizer is a deep learning model that classifies flower images, specifically recognizing Rose, Sunflower, and Tulip. It allows users to upload images for real-time classification and offers batch processing for enhanced performance.

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