Our Fire Dragon Fruit Growth Trend Detection project is built on the basis of Fire Dragon Fruit data. Through learning, you can deploy your AI service to the cloud to achieve the ability to recognize Fire Dragon Fruit growth trends in the cloud. Below are the tasks we have completed: Task 1: Preparation of Fire Dragon Fruit Training Dataset (Target Detection Image Annotation Using Sprite Labeling Assistant, Transforming Training and Validation Dataset into Tfrecord Format Dataset) Task 2: Building and Training of Target Detection Model (Understanding Target Detection, YOLOv3 Target Detection Model, Tensorflow YOLOv3 Model Training) Task 3: Growth Trend Model Inference and Evaluation (Crop Growth Trend Model Inference Interface, Crop Growth Trend Model Inference Code Implementation, Crop Growth Trend Model Accuracy Evaluation) Task 4: Growth Trend AI Model Service Packaging (Restful API, Flask Environment Set-up, Flask Implementation of Fire Dragon Fruit Growth Trend AI Service) Task 5: Model Cloud Deployment and Installation (Growth Trend AI Service Runtime Environment Configuration, Writing Automation Installation Script to Achieve One-key Installation and Activation of Service).