Today, it is not uncommon for there to be many vehicles in a city. This is due to the fact that there is a significant number of people who have the freedom to move around and travel, as well as the fact that there are too many vehicles in the city.
For developers who devise applications for insurance adjusters who need to find out the characteristics of a wreckage, the best option is a vehicle damage detector API to ease down the process for API development and for API usage.
There are many ways in which an insurance adjuster can use Vehicle Damage Detector API. The first and most obvious way is to use it to assess vehicle damage automatically, so the adjuster doesn’t have to do it manually. This can save a lot of time and effort, since they don’t have to inspect all the vehicles they need to evaluate manually. Another way is this API which provides accurate and up-to-date information on vehicle damage. This means that they will be able to assess the damage more accurately and efficiently, which will help them make accurate claims for their clients.
How Does An API Help An Insurance Adjuster?
There are many ways. The first way is that it can help render information about the type of damage and its location on the vehicle. Another way is by saving time as the API can do all of the work for them. Finally, an API can also help an insurance adjuster by providing them with up-to-date information. This is because an API can furnish data about both new and old vehicles, which means that the adjuster will always have access to the latest figures.
How Does A Vehicle Damage Detector API Work?
Vehicle Damage Detector API works by sending an image of a vehicle to the API and then outputting a list of all of the types of damage that are present in it. This way one can easily identify all the different types of damage, and their location on the vehicle, without having to inspect each car separately.
Additionally, this API is very easy to use, by just providing the image URL to receive a list of all damage in that vehicle. All adjusters need a tool like this to save precious time and effort when assessing vehicle damage.
More About Vehicle Damage Detector API
This API allows to identify which type of damage each vehicle, the location in the car, and the cost of the spare part or the repair, i.e. that assessing how much money should be paid by the insurance company is accurately drawn by the API.
Counting on a subscription on Zyla API Hub marketplace, just start using, connecting and managing APIs. Subscribe to the Vehicle Damage Detector API by simply clicking on the button “Start Free Trial”. Then meet your needed endpoint and simply provide the picture of the damaged car. Make the API call by pressing the button “test endpoint” and see the results on display. The AI will process and retrieve a response from the analysis of the input picture.
It`s advisable to keep the input image under 5MB, between 2000x2000 and 640x480 in resolution for a more accurate response. To avoid longer process times it´s recommended not to use higher resolution images. For best damage detection, it’s recommended to take a close picture of the area, approx. 80cm – 1.5m when taking the picture.
If the input is “draw_result”: true,
“image”: “https://i.insider.com/54da54336bb3f7156eeef89e?width=800&format=jpeg”, the result will look like this:
{
"draw_result": true,
"job_id": "7512d7a2-91f1-424c-a464-67c3662af438",
"output": {
"elements": [
{
"bbox": [
368,
150,
485,
242
],
"damage_category": "slight_scratch",
"damage_color": [
50,
50,
100
],
"damage_id": "1",
"damage_location": "rear_bumper",
"score": 0.569186
},
{
"bbox": [
331,
415,
439,
478
],
"damage_category": "slight_scratch",
"damage_color": [
50,
50,
100
],
"damage_id": "1",
"damage_location": "rear_bumper",
"score": 0.485635
},
{
"bbox": [
405,
311,
488,
381
],
"damage_category": "slight_scratch",
"damage_color": [
50,
50,
100
],
"damage_id": "1",
"damage_location": "right_rear_tire",
"score": 0.354201
},
{
"bbox": [
402,
309,
490,
382
],
"damage_category": "severe_scratch",
"damage_color": [
0,
0,
120
],
"damage_id": "2",
"damage_location": "right_rear_tire",
"score": 0.637032
},
{
"bbox": [
331,
415,
439,
478
],
"damage_category": "severe_scratch",
"damage_color": [
0,
0,
120
],
"damage_id": "2",
"damage_location": "rear_bumper",
"score": 0.41991
},
{
"bbox": [
369,
154,
468,
232
],
"damage_category": "severe_scratch",
"damage_color": [
0,
0,
120
],
"damage_id": "2",
"damage_location": "rear_bumper",
"score": 0.337978
}
]
},
"output_url": "https://vapistorage.blob.core.windows.net/vapi/vehicle-damage/draw-094355.422277-7512d7a2-91f1-424c-a464-67c3662af438.jpg?se=2023-04-21T09%3A44%3A55Z&sp=rt&sv=2020-10-02&sr=b&sig=JjCtxcqkh%2Bw3PX7BIeQPUwkjxZ7ncV%2BfpKYDVnnA290%3D",
"url_expiry": "2023/04/21 09:44:55"
}