Dataset Cabai Computer Vision Project

Here are a few use cases for this project:

1. Agricultural Monitoring: The Dataset Cabai model could be used to monitor and analyze the germination stages of chili pepper crops. Farmers can assess the seedling tray images to identify Tidak Berkecambah (non-germinated), Daun_Kotiledon (cotyledon leaves), and Berkecambah (germinated) seeds, allowing them to make better decisions about seedling health, fertilization, and transplantation.

2. Smart Greenhouse Systems: Implementing the Dataset Cabai model in a smart greenhouse could enable automation in the control of temperature, humidity, and light exposure based on the observed germination growth stages. This will allow for optimization of plant growth and improved efficiency in the management of resources such as energy and water.

3. Seed Quality Control: Seed manufacturers can incorporate the Dataset Cabai model into their quality control process by testing a sample of seeds for their germination potential. Using automated image analysis, the model can provide more accurate and quicker results, leading to more reliable seed batches in the market.

4. Horticultural Education and Research: The Dataset Cabai model can be employed as an educational tool for teaching students and researchers about chili pepper germination and growth. By analyzing images, individuals can learn to identify and understand different growth stages, allowing for better experimentation and research in the horticulture field.

5. Automated Chili Seed Sorting: By integrating the Dataset Cabai model into seed sorting equipment, companies can automate the sorting process based on germination quality. The model would identify Tidak Berkecambah seeds for removal from the batch, ensuring that only seeds with high potential for germination are sold or further cultivated.