Nature Image Classification Model

I’m putting together an end-to-end computer-vision pipeline that can automatically recognise and classify nature and landscape photographs. The core goal is a reliable image-classification model that can take a raw photo—forest, desert, coastline, mountain range, or any other natural scene we decide on—and return the correct label with strong accuracy.

Here’s what I need from you:
• A well-structured dataset or clear guidance on sourcing and curating one (public sets are fine as long as licensing is respected).
• A training workflow in Python using a mainstream framework such as TensorFlow or PyTorch, complete with data-augmentation, fine-tuning, and validation steps.
• Trained model weights plus inference code that runs on CPU or GPU with a single command.
• A concise README explaining environment setup, training parameters, and how to add new classes later.
• Evaluation metrics (precision, recall, confusion matrix) so I can judge performance quickly.

Acceptance will be based on reproducible training, cleanly commented code, and meeting an agreed-upon accuracy threshold on a held-out test set. If you’ve tackled similar nature-scene projects or have transfer-learning tricks up your sleeve, let’s get started—I’m ready to move fast once you are.