Welcome to the Plant Recognition project! This repository showcases a plant recognition model based on the powerful MobileNetV2 architecture using TensorFlow and Keras. The model is designed to identify various plant species, making it a valuable tool for plant enthusiasts and researchers.

• Introduction
• Setup
• Data Preparation
• Training
• Inference
• Results
• Dependencies
• License

Do you ever wonder about the species of plants around you? The Plant Recognition with MobileNetV2 project is here to help! Our solution leverages the MobileNetV2 architecture, a state-of-the-art deep learning model, to classify various plant species based on images. This repository provides code for training, fine-tuning, and making predictions using the model.

To dive into the world of plant recognition, follow these simple steps:

1. Install Dependencies:

   pip install tensorflow opencv-python matplotlib

2. Clone the Repository:

   git clone https://github.com/your-username/plant-recognition.git
   cd plant-recognition

Prepare your own custom dataset to unleash the full potential of plant recognition. Organize your data as follows:

your-custom-dataset/
|-- train/
|   |-- class_1/
|   |   |-- image1.jpg
|   |   |-- image2.jpg
|   |-- class_2/
|   |   |-- image3.jpg
|   |   |-- image4.jpg
|-- test/
|   |-- class_1/
|   |   |-- image5.jpg
|   |   |-- image6.jpg
|   |-- class_2/
|   |   |-- image7.jpg
|   |   |-- image8.jpg

Adjust the paths in the code according to your dataset structure.

Train the model by executing the training script:

python train.py

Feel free to tweak the hyperparameters in the script to achieve the best results.

See the magic happen with the inference script:

python inference.py --image_path path/to/your/image.jpg

Replace path/to/your/image.jpg with the path to the image you want to classify.

Visualize the training and validation metrics using the provided scripts. Marvel at the accuracy and gain insights into the recognition capabilities of your model.

• TensorFlow
• OpenCV
• Matplotlib

This project is licensed under the MIT License.

Ready to embark on a journey of discovery? Start recognizing plants with our cutting-edge model today! 🌱✨