Here, we are going to build our own ML model using TensorFlow to analyze the damage level of the vehicle. We need to be careful in picking the dataset that will play a crucial part in the damage evaluation phase. Here are the steps that we are going to follow in order to build the model:

1. Find the image dataset of the damaged vehicles.
2. Categorize the images based on their damage levels. First, we need to identify that the object in the picture is actually a car. To do that, we need to have two categories of image sets that do and do not have cars in them. Then, we need to have three more categories to find the damage level of the cars categorized under high, medium, or low levels. Make sure that you have at least 1,000+ images under each of the five categories. Once the dataset is ready, we are ready to train our model.
3. We will train our model using TensorFlow.
4. We will build a web application to analyze the damage level of the vehicle.
5. Update the result.