Object detection problem

Project Title: Object detection problem

Objective:
Develop an object detection system with a high level of accuracy to detect garbage objects.

Requirements:
- Expertise in computer vision and object detection algorithms
- Proficiency in machine learning and deep learning frameworks
- Experience with training models using specific datasets
- Ability to handle large datasets and preprocess images
- Strong programming skills in Python
- Familiarity with popular libraries and frameworks such as TensorFlow, PyTorch, or OpenCV

Tasks:
1. Dataset Preparation:
- Utilize the provided dataset to train the object detection model
- Preprocess the images and annotate the garbage objects for training

2. Model Training:
- Implement state-of-the-art object detection algorithms
- Fine-tune the model using transfer learning techniques
- Optimize the model for high accuracy and minimal false positives

3. Evaluation and Iteration:
- Evaluate the model's performance using validation datasets
- Identify and resolve any issues or limitations in the detection system
- Continuously improve the model through iterative training and fine-tuning

Deliverables:
- Trained object detection model capable of accurately detecting garbage objects
- Documentation detailing the model architecture, training process, and evaluation results

Note:
- The expected accuracy for the detection system is